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MainWindow.py
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import pickle
from PyQt5.QtGui import QIcon
from sklearn import exceptions as skex
from sklearn.linear_model import LinearRegression
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.naive_bayes import MultinomialNB
from sklearn.naive_bayes import BernoulliNB
from sklearn.model_selection import GridSearchCV
from sklearn import datasets
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QFileDialog
from PyQt5.QtWidgets import QMessageBox
from DecisionTree import Ui_DT
from KNeighbours import Ui_KNN
from RandomForest import Ui_RF
from SVM import Ui_SVM
from LogisticRegression import Ui_LR
from CHPT import Ui_CHPT
from HPT import Ui_HPT
from Target import Ui_Target
import pandas as pd
import time
class Ui_MainWindow(object):
def __init__(self):
super().__init__()
self.x = []
self.y = []
self.model = None; self.output = []
self.df = pd.DataFrame()
self.col = ""
self.path = ""
self.SVMValues = {}; self.DTValues = {}; self.KNNValues = {}; self.RTValues = {}; self.LRValues = {};
self.CHPTDM = QtWidgets.QDialog(); self.CHPTOM = Ui_CHPT(); self.CHPTOM.setupUi(self.CHPTDM)
self.HPTDM = QtWidgets.QDialog(); self.HPTOM = Ui_HPT(); self.HPTOM.setupUi(self.HPTDM)
self.SVMDM = QtWidgets.QDialog(); self.SVMOM = Ui_SVM(); self.SVMOM.setupUi(self.SVMDM)
self.DTDM = QtWidgets.QDialog(); self.DTOM = Ui_DT(); self.DTOM.setupUi(self.DTDM)
self.KNNDM = QtWidgets.QDialog(); self.KNNOM = Ui_KNN(); self.KNNOM.setupUi(self.KNNDM)
self.RTDM = QtWidgets.QDialog(); self.RTOM = Ui_RF(); self.RTOM.setupUi(self.RTDM)
self.LRDM = QtWidgets.QDialog(); self.LRM = Ui_LR(); self.LRM.setupUi(self.LRDM)
self.TRDM = QtWidgets.QDialog(); self.TRM = Ui_Target(); self.TRM.setupUi(self.TRDM)
self.CHPTOM.NB.stateChanged.connect(self.NaivesBayes)
self.SVMVal(); self.LRVal(); self.DTVal(); self.KNNVal(); self.RTVal()
self.CHPTValues = {
'SVM': self.SVMValues,
'DecisionTree': self.DTValues,
'KNearestNeighbours':self.KNNValues,
'RandomForest':self.RTValues
}
self.HPTValues = { 'Logistic Regression':self.LRValues }
self.SVMOM.Apply.clicked.connect(self.SVMVal)
self.DTOM.Apply.clicked.connect(self.DTVal)
self.KNNOM.Apply.clicked.connect(self.KNNVal)
self.RTOM.Apply.clicked.connect(self.RTVal)
self.LRM.Apply.clicked.connect(self.LRVal)
self.CHPTOM.Apply.clicked.connect(self.CHPTVal)
self.HPTOM.Apply.clicked.connect(self.HPTVal)
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.setFixedSize(843, 665)
font = QtGui.QFont()
font.setPointSize(10)
MainWindow.setFont(font)
icon = QtGui.QIcon()
icon.addPixmap(QtGui.QPixmap(":/images/1.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
MainWindow.setWindowIcon(icon)
MainWindow.setStyleSheet("border-image: url(:/images/MainBackGround.jpg);")
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.setObjectName("centralwidget")
self.gridLayout = QtWidgets.QGridLayout(self.centralwidget)
self.gridLayout.setObjectName("gridLayout")
self.verticalLayout = QtWidgets.QVBoxLayout()
self.verticalLayout.setObjectName("verticalLayout")
self.Logo = QtWidgets.QLabel(self.centralwidget)
self.Logo.setMinimumSize(QtCore.QSize(771, 121))
font = QtGui.QFont()
font.setPointSize(10)
self.Logo.setFont(font)
self.Logo.setStyleSheet("border-image: url(:/images/Logo.png);")
self.Logo.setText("")
self.Logo.setObjectName("Logo")
self.verticalLayout.addWidget(self.Logo)
self.msg1 = QtWidgets.QLabel(self.centralwidget)
self.msg1.setMinimumSize(QtCore.QSize(181, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.msg1.setFont(font)
self.msg1.setStyleSheet("border-image: url(:/images/1WhiteTransparent.png);")
self.msg1.setScaledContents(True)
self.msg1.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.msg1.setObjectName("msg1")
self.verticalLayout.addWidget(self.msg1)
self.horizontalLayout = QtWidgets.QHBoxLayout()
self.horizontalLayout.setObjectName("horizontalLayout")
spacerItem = QtWidgets.QSpacerItem(138, 28, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout.addItem(spacerItem)
self.FilePath = QtWidgets.QLabel(self.centralwidget)
self.FilePath.setMinimumSize(QtCore.QSize(497, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.FilePath.setFont(font)
self.FilePath.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);\n"
"border-radius: 6;")
self.FilePath.setText("")
self.FilePath.setScaledContents(True)
self.FilePath.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.FilePath.setObjectName("FilePath")
self.horizontalLayout.addWidget(self.FilePath)
spacerItem1 = QtWidgets.QSpacerItem(168, 28, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout.addItem(spacerItem1)
self.verticalLayout.addLayout(self.horizontalLayout)
spacerItem2 = QtWidgets.QSpacerItem(798, 28, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed)
self.verticalLayout.addItem(spacerItem2)
self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
spacerItem3 = QtWidgets.QSpacerItem(78, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_2.addItem(spacerItem3)
self.DisplayData = QtWidgets.QPushButton(self.centralwidget)
self.DisplayData.setMinimumSize(QtCore.QSize(151, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.DisplayData.setFont(font)
self.DisplayData.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);\n"
"border-radius: 6;")
self.DisplayData.setObjectName("DisplayData")
self.horizontalLayout_2.addWidget(self.DisplayData)
spacerItem4 = QtWidgets.QSpacerItem(18, 28, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_2.addItem(spacerItem4)
self.EditData = QtWidgets.QComboBox(self.centralwidget)
self.EditData.setMinimumSize(QtCore.QSize(151, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.EditData.setFont(font)
self.EditData.setLayoutDirection(QtCore.Qt.LeftToRight)
self.EditData.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.EditData.setObjectName("EditData")
self.EditData.addItem("")
self.EditData.addItem("")
self.EditData.addItem("")
self.horizontalLayout_2.addWidget(self.EditData)
spacerItem5 = QtWidgets.QSpacerItem(18, 28, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_2.addItem(spacerItem5)
self.DescribeDate = QtWidgets.QPushButton(self.centralwidget)
self.DescribeDate.setMinimumSize(QtCore.QSize(151, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.DescribeDate.setFont(font)
self.DescribeDate.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);\n"
"border-radius: 6;")
self.DescribeDate.setObjectName("DescribeDate")
self.horizontalLayout_2.addWidget(self.DescribeDate)
spacerItem6 = QtWidgets.QSpacerItem(118, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_2.addItem(spacerItem6)
self.verticalLayout.addLayout(self.horizontalLayout_2)
spacerItem7 = QtWidgets.QSpacerItem(798, 28, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed)
self.verticalLayout.addItem(spacerItem7)
self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
self.horizontalLayout_4.setObjectName("horizontalLayout_4")
spacerItem8 = QtWidgets.QSpacerItem(158, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_4.addItem(spacerItem8)
self.FeatureTuning = QtWidgets.QPushButton(self.centralwidget)
self.FeatureTuning.setMinimumSize(QtCore.QSize(151, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.FeatureTuning.setFont(font)
self.FeatureTuning.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);\n"
"border-radius: 6;")
self.FeatureTuning.setObjectName("FeatureTuning")
self.horizontalLayout_4.addWidget(self.FeatureTuning)
spacerItem9 = QtWidgets.QSpacerItem(18, 28, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_4.addItem(spacerItem9)
self.DropBox = QtWidgets.QComboBox(self.centralwidget)
self.DropBox.setMinimumSize(QtCore.QSize(151, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.DropBox.setFont(font)
self.DropBox.setLayoutDirection(QtCore.Qt.LeftToRight)
self.DropBox.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.DropBox.setObjectName("DropBox")
self.DropBox.addItem("")
self.DropBox.addItem("")
self.DropBox.addItem("")
self.horizontalLayout_4.addWidget(self.DropBox)
spacerItem10 = QtWidgets.QSpacerItem(238, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_4.addItem(spacerItem10)
self.verticalLayout.addLayout(self.horizontalLayout_4)
spacerItem11 = QtWidgets.QSpacerItem(795, 58, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed)
self.verticalLayout.addItem(spacerItem11)
self.msg2 = QtWidgets.QLabel(self.centralwidget)
self.msg2.setMinimumSize(QtCore.QSize(191, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.msg2.setFont(font)
self.msg2.setStyleSheet("border-image: url(:/images/1WhiteTransparent.png);")
self.msg2.setScaledContents(True)
self.msg2.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.msg2.setObjectName("msg2")
self.verticalLayout.addWidget(self.msg2)
self.horizontalLayout_6 = QtWidgets.QHBoxLayout()
self.horizontalLayout_6.setObjectName("horizontalLayout_6")
spacerItem12 = QtWidgets.QSpacerItem(28, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_6.addItem(spacerItem12)
self.ModelType = QtWidgets.QComboBox(self.centralwidget)
self.ModelType.setMinimumSize(QtCore.QSize(181, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.ModelType.setFont(font)
self.ModelType.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.ModelType.setObjectName("ModelType")
self.ModelType.addItem("")
self.ModelType.addItem("")
self.ModelType.addItem("")
self.horizontalLayout_6.addWidget(self.ModelType)
self.RegressionType = QtWidgets.QComboBox(self.centralwidget)
self.RegressionType.setEnabled(True)
self.RegressionType.setMinimumSize(QtCore.QSize(201, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.RegressionType.setFont(font)
self.RegressionType.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.RegressionType.setObjectName("RegressionType")
self.RegressionType.addItem("")
self.RegressionType.addItem("")
self.RegressionType.addItem("")
self.RegressionType.addItem("")
self.horizontalLayout_6.addWidget(self.RegressionType)
self.ClassificationType = QtWidgets.QComboBox(self.centralwidget)
self.ClassificationType.setMinimumSize(QtCore.QSize(201, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.ClassificationType.setFont(font)
self.ClassificationType.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.ClassificationType.setObjectName("ClassificationType")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.ClassificationType.addItem("")
self.horizontalLayout_6.addWidget(self.ClassificationType)
self.ClassificationTypeNB = QtWidgets.QComboBox(self.centralwidget)
self.ClassificationTypeNB.setMinimumSize(QtCore.QSize(141, 31))
font = QtGui.QFont()
font.setPointSize(10)
self.ClassificationTypeNB.setFont(font)
self.ClassificationTypeNB.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.ClassificationTypeNB.setObjectName("ClassificationTypeNB")
self.ClassificationTypeNB.addItem("")
self.ClassificationTypeNB.addItem("")
self.ClassificationTypeNB.addItem("")
self.horizontalLayout_6.addWidget(self.ClassificationTypeNB)
spacerItem13 = QtWidgets.QSpacerItem(28, 28, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
self.horizontalLayout_6.addItem(spacerItem13)
self.verticalLayout.addLayout(self.horizontalLayout_6)
spacerItem14 = QtWidgets.QSpacerItem(808, 38, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed)
self.verticalLayout.addItem(spacerItem14)
self.horizontalLayout_3 = QtWidgets.QHBoxLayout()
self.horizontalLayout_3.setObjectName("horizontalLayout_3")
self.progressBar = QtWidgets.QProgressBar(self.centralwidget)
self.progressBar.setMinimumSize(QtCore.QSize(729, 31))
font = QtGui.QFont()
font.setPointSize(12)
self.progressBar.setFont(font)
self.progressBar.setLayoutDirection(QtCore.Qt.LeftToRight)
self.progressBar.setStyleSheet("border-image: url(:/images/1WhiteTransparent.png);")
self.progressBar.setProperty("value", 0)
self.progressBar.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.progressBar.setObjectName("progressBar")
self.horizontalLayout_3.addWidget(self.progressBar)
self.Train = QtWidgets.QPushButton(self.centralwidget)
self.Train.setMinimumSize(QtCore.QSize(81, 31))
font = QtGui.QFont()
font.setPointSize(12)
self.Train.setFont(font)
self.Train.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);\n"
"border-radius: 6;")
self.Train.setObjectName("Train")
self.horizontalLayout_3.addWidget(self.Train)
self.verticalLayout.addLayout(self.horizontalLayout_3)
spacerItem15 = QtWidgets.QSpacerItem(818, 28, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed)
self.verticalLayout.addItem(spacerItem15)
self.gridLayout.addLayout(self.verticalLayout, 0, 0, 1, 1)
MainWindow.setCentralWidget(self.centralwidget)
self.menuBar = QtWidgets.QMenuBar(MainWindow)
self.menuBar.setGeometry(QtCore.QRect(0, 0, 843, 26))
self.menuBar.setStyleSheet("border-image: url(:/images/1WhiteBackground.jpg);")
self.menuBar.setObjectName("menuBar")
self.menuFile = QtWidgets.QMenu(self.menuBar)
self.menuFile.setObjectName("menuFile")
self.menuSave = QtWidgets.QMenu(self.menuFile)
self.menuSave.setObjectName("menuSave")
self.menuHelp = QtWidgets.QMenu(self.menuBar)
self.menuHelp.setObjectName("menuHelp")
MainWindow.setMenuBar(self.menuBar)
self.actionData_Cleaning = QtWidgets.QAction(MainWindow)
self.actionData_Cleaning.setObjectName("actionData_Cleaning")
self.actionModel_Training = QtWidgets.QAction(MainWindow)
self.actionModel_Training.setObjectName("actionModel_Training")
self.actionVersion = QtWidgets.QAction(MainWindow)
self.actionVersion.setObjectName("actionVersion")
self.actionAbout = QtWidgets.QAction(MainWindow)
self.actionAbout.setObjectName("actionAbout")
self.actionOpen = QtWidgets.QAction(MainWindow)
self.actionOpen.setObjectName("actionOpen")
self.actionAbout_2 = QtWidgets.QAction(MainWindow)
self.actionAbout_2.setObjectName("actionAbout_2")
self.actionAbout_Model_Traning = QtWidgets.QAction(MainWindow)
self.actionAbout_Model_Traning.setObjectName("actionAbout_Model_Traning")
self.actionAs_CSV = QtWidgets.QAction(MainWindow)
self.actionAs_CSV.setObjectName("actionAs_CSV")
self.actionAs_PDF = QtWidgets.QAction(MainWindow)
self.actionAs_PDF.setObjectName("actionAs_PDF")
self.actionExit = QtWidgets.QAction(MainWindow)
self.actionExit.setObjectName("actionExit")
self.actionPredict = QtWidgets.QAction(MainWindow)
self.actionPredict.setObjectName("actionPredict")
self.actionSave = QtWidgets.QAction(MainWindow)
self.actionSave.setObjectName("actionSave")
self.menuSave.addAction(self.actionAs_CSV)
self.menuSave.addSeparator()
self.menuSave.addAction(self.actionAs_PDF)
self.menuFile.addAction(self.actionSave)
self.menuFile.addSeparator()
self.menuFile.addAction(self.menuSave.menuAction())
self.menuFile.addSeparator()
self.menuFile.addAction(self.actionOpen)
self.menuFile.addSeparator()
self.menuFile.addAction(self.actionPredict)
self.menuFile.addSeparator()
self.menuFile.addAction(self.actionExit)
self.menuHelp.addAction(self.actionAbout_2)
self.menuHelp.addSeparator()
self.menuHelp.addAction(self.actionAbout_Model_Traning)
self.menuBar.addAction(self.menuFile.menuAction())
self.menuBar.addAction(self.menuHelp.menuAction())
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
self.RegressionType.setHidden(True)
self.ClassificationType.setHidden(True)
self.ClassificationTypeNB.setHidden(True)
self.ModelType.currentIndexChanged.connect(self.mtype)
self.ClassificationType.currentIndexChanged.connect(self.ctype)
self.RegressionType.currentIndexChanged.connect(self.Regression)
self.Train.clicked.connect(self.ModelTrain)
self.actionPredict.triggered.connect(self.predict)
self.actionExit.triggered.connect(self.Quit)
self.RegressionType.currentIndexChanged.connect(self.TrainModelR)
self.ClassificationTypeNB.currentIndexChanged.connect(self.ntype)
self.actionAs_CSV.setText("Save Cleaned Data")
self.actionAs_PDF.setText("Save Predicted Data")
self.actionAs_CSV.triggered.connect(self.SaveCD)
self.actionAs_PDF.triggered.connect(self.SavePD)
self.actionSave.triggered.connect(self.SaveDF)
''' ComboBoxes '''
def NaivesBayes(self):
self.progressBar.setValue(0)
self.model = None
if(self.CHPTOM.NB.isChecked()):
self.CHPTOM.GNB.setVisible(True); self.CHPTOM.GNBLabel.setVisible(True)
self.CHPTOM.BNB.setVisible(True); self.CHPTOM.BNBLabel.setVisible(True)
self.CHPTOM.MNB.setVisible(True); self.CHPTOM.MNBLabel.setVisible(True)
self.CHPTDM.setFixedHeight(260)
else:
self.CHPTOM.GNB.setVisible(False); self.CHPTOM.GNBLabel.setVisible(False); self.CHPTOM.GNB.setChecked(False)
self.CHPTOM.BNB.setVisible(False); self.CHPTOM.BNBLabel.setVisible(False); self.CHPTOM.BNB.setChecked(False)
self.CHPTOM.MNB.setVisible(False); self.CHPTOM.MNBLabel.setVisible(False); self.CHPTOM.MNB.setChecked(False)
self.CHPTDM.setFixedHeight(200)
self.model = None
def ntype(self):
self.progressBar.setValue(0)
self.model = None
if self.ClassificationTypeNB.currentIndex() == 0:
self.model = GaussianNB()
elif self.ClassificationTypeNB.currentIndex() == 1:
self.model = BernoulliNB()
elif self.ClassificationTypeNB.currentIndex() == 2:
self.model = MultinomialNB()
else:
self.model = None
def ctype(self):
self.progressBar.setValue(0)
self.model = None
if self.ClassificationType.currentIndex() == 0:
self.model = None
self.ClassificationTypeNB.setCurrentIndex(0); self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
elif self.ClassificationType.currentIndex() == 1:
self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
self.SVMDM.show()
if (self.SVMDM.exec_()):
self.model = GridSearchCV(SVC(), self.SVMValues, cv=2, return_train_score=False)
else:
self.model = None
self.SVMDM.close()
elif self.ClassificationType.currentIndex() == 2:
self.ClassificationTypeNB.setVisible(True); self.RegressionType.setHidden(True)
elif self.ClassificationType.currentIndex() == 3:
self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
self.DTDM.show()
if(self.DTDM.exec_()):
self.model = GridSearchCV(DecisionTreeClassifier(), self.DTValues, cv=2, return_train_score=False)
else:
self.model = None
self.DTDM.close()
elif self.ClassificationType.currentIndex() == 4:
self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
self.RTDM.show()
if(self.RTDM.exec_()):
self.model = GridSearchCV(RandomForestClassifier(), self.RTValues, cv=2, return_train_score=False)
else:
self.model = None
self.RTDM.close()
elif self.ClassificationType.currentIndex() == 5:
self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
self.KNNDM.show()
if(self.KNNDM.exec_()):
self.model = GridSearchCV(KNeighborsClassifier(), self.KNNValues, cv=2, return_train_score=False)
else:
self.model = None
self.KNNDM.close()
elif self.ClassificationType.currentIndex() == 6:
bestscore = {}
self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
self.CHPTDM.show()
if(self.CHPTDM.exec_()):
if self.CHPTOM.SVM.isChecked():
self.model = GridSearchCV(SVC(), self.CHPTOM.SVMValues, cv=2, return_train_score=False)
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 1
if self.CHPTOM.DT.isChecked():
self.model = GridSearchCV(DecisionTreeClassifier(), self.CHPTOM.DTValues, cv=2, return_train_score=False)
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 2
if self.CHPTOM.RT.isChecked():
self.model = GridSearchCV(RandomForestClassifier(), self.CHPTOM.RTValues, cv=2, return_train_score=False)
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 4
if self.CHPTOM.KNN.isChecked():
self.model = GridSearchCV(KNeighborsClassifier(), self.CHPTOM.KNNValues, cv=2, return_train_score=False)
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 3
if self.CHPTOM.NB.isChecked():
if self.CHPTOM.BNB.isChecked():
self.model = BernoulliNB()
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 6
if self.CHPTOM.MNB.isChecked():
self.model = MultinomialNB()
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 7
if self.CHPTOM.GNB.isChecked():
self.model = GaussianNB()
self.model.fit(self.x, self.y)
bestscore[round(self.model.score(self.x, self.y)*100)] = 5
try:
self.maxscore = max(bestscore.keys())
model_list = [0,
GridSearchCV(SVC(), self.CHPTOM.SVMValues, cv=2, return_train_score=False),
GridSearchCV(DecisionTreeClassifier(), self.CHPTOM.DTValues, cv=2, return_train_score=False),
GridSearchCV(KNeighborsClassifier(), self.CHPTOM.KNNValues, cv=2, return_train_score=False),
GridSearchCV(RandomForestClassifier(), self.CHPTOM.RTValues, cv=2, return_train_score=False),
GaussianNB(), BernoulliNB(), MultinomialNB()
]
self.model = model_list[bestscore[self.maxscore]]
except ValueError:
self.model = None
else:
self.model = None
self.CHPTDM.close()
def mtype(self):
self.progressBar.setValue(0)
self.model = None
if self.ModelType.currentIndex() == 0:
self.model = None
self.RegressionType.setCurrentIndex(0); self.ClassificationType.setCurrentIndex(0); self.ClassificationTypeNB.setCurrentIndex(0)
self.RegressionType.setHidden(True); self.ClassificationType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
elif self.ModelType.currentIndex() == 1:
self.model = None
self.ClassificationType.setCurrentIndex(0); self.ClassificationTypeNB.setCurrentIndex(0)
self.RegressionType.setVisible(True); self.ClassificationType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
elif self.ModelType.currentIndex() == 2:
self.model = None
self.RegressionType.setCurrentIndex(0); self.ClassificationTypeNB.setCurrentIndex(0)
self.ClassificationType.setVisible(True); self.RegressionType.setHidden(True); self.ClassificationTypeNB.setHidden(True)
def Regression(self):
self.progressBar.setValue(0)
self.model = None
if self.RegressionType.currentIndex() == 0:
self.model = None
elif self.RegressionType.currentIndex() == 1:
self.model = LinearRegression()
elif self.RegressionType.currentIndex() == 2:
self.LRDM.show()
if (self.LRDM.exec_()):
self.model = GridSearchCV(LogisticRegression(), self.LRValues, cv=2 ,return_train_score=False)
else:
self.model = None
self.LRDM.close()
elif self.RegressionType.currentIndex() == 3:
self.HPTDM.show()
if (not self.HPTDM.exec_()):
self.model = None
self.HPTDM.close()
''' Model training & Prediction'''
def TrainModelR(self):
self.model = None
if self.RegressionType.currentIndex() == 1:
self.model = LinearRegression()
elif self.RegressionType.currentIndex() == 2:
self.model = GridSearchCV(LogisticRegression(), self.LRValues, cv=2 ,return_train_score=False)
elif self.RegressionType.currentIndex() == 3:
try:
if self.HPTValues['Linear Regression'] == True and self.HPTValues['LogisticR'] == True:
self.Li = LinearRegression()
self.Li.fit(self.x, self.y)
LIScore = round(self.Li.score(self.x, self.y) * 100)
self.Lo = GridSearchCV(LogisticRegression(), self.HPTValues['Logistic Regression'], cv=5 ,return_train_score=False)
self.Lo.fit(self.x , self.y)
LOScore = round(self.Lo.best_score_ * 100)
if LOScore > LIScore:
self.model = self.Lo
else:
self.model = self.Li
elif self.HPTValues['Linear Regression'] == True:
self.model = LinearRegression()
elif self.HPTValues['LogisticR'] == True:
self.model = GridSearchCV(LogisticRegression(), self.LRValues, cv=2 ,return_train_score=False)
else:
self.model = None
self.HPTDM.close()
except KeyError:
print()
def TrainModel(self):
self.ModelTrain()
def LOADDataFrame(self):
pickle_in = open("DataFrame\\DataFrame.pickle","rb")
data = pickle.load(pickle_in)
self.TRDM.show()
self.TRM.TargetBox.addItems(data.columns.tolist())
if self.TRDM.exec_() == 1:
try:
temp_df = data.copy()
self.x = temp_df.drop(self.TRM.TargetBox.currentText(), 1)
self.y = temp_df[self.TRM.TargetBox.currentText()]
self.col = self.TRM.TargetBox.currentText()
self.x, self.xt, self.y, self.yt = train_test_split(self.x, self.y, test_size = 0.2)
self.TRDM.accept()
except ValueError:
self.TRDM.close()
def ModelTrain(self):
if not (self.model == None):
self.LOADDataFrame()
self.model.fit(self.x , self.y)
for i in range(0,101,1):
self.progressBar.setValue(i)
time.sleep(0.1)
else:
msg = QMessageBox()
msg.setWindowTitle("Warning")
msg.setText("Cannot Train Model")
msg.setIcon(QMessageBox.Warning)
msg.setDetailedText("You didn't select any model to train on.")
msg.setWindowIcon(QtGui.QIcon('Images/Warning.png'))
msg.exec_()
def predict(self):
if(self.model == None):
self.output = []
msg = QMessageBox()
msg.setWindowTitle("Warning")
msg.setText("Cannot Predict")
msg.setIcon(QMessageBox.Warning)
msg.setDetailedText("You didn't train any model to predict on.")
msg.setWindowIcon(QtGui.QIcon('Images/Warning.png'))
msg.exec_()
else:
try:
self.output = self.model.predict(self.x)
except skex.NotFittedError:
print()
''' MenuButton Functions '''
def Quit(self):
exit()
def SaveCD(self):
print()
def SavePD(self):
if not (len(self.output) == 0):
self.df[self.col] = self.output
filename = QFileDialog.getSaveFileName()
if not (len(filename[0]) == 0):
self.path = filename[0]
self.df.to_csv(self.path + '.csv', index=False)
else:
msg = QMessageBox()
msg.setWindowTitle("Warning")
msg.setText("Cannot Save Predicted File")
msg.setIcon(QMessageBox.Warning)
msg.setDetailedText("You didn't predict the values.")
msg.setWindowIcon(QtGui.QIcon('Images/Warning.png'))
msg.exec_()
''' Taking Values from dialog box '''
def LRVal(self):
penalty = self.LRM.penaltylist.currentText()
solver = self.LRM.solverlist.currentText()
multi_class = self.LRM.multiclasslist.currentText()
C = self.LRM.CdoubleSpinBox.value()
max_iter = self.LRM.max_tierspinBox.value()
n_jobs = self.LRM.n_jobsspinBox.value()
dual = self.LRM.dualcheckBox.isChecked()
warm_start = self.LRM.warmstartcheckBox.isChecked()
fit_intercept = self.LRM.fitinterceptcheckBox.isChecked()
self.LRValues = {
'penalty':[penalty],
'solver':[solver],
'multi_class':[multi_class],
'C':[C],
'max_iter':[max_iter],
'n_jobs':[n_jobs],
'dual':[dual],
'warm_start':[warm_start],
'fit_intercept':[fit_intercept]
}
self.LRDM.accept()
def SVMVal(self):
kernel = self.SVMOM.kernellist.currentText()
gamma = self.SVMOM.gammalist.currentText()
dfs = self.SVMOM.decision_function_shapelist.currentText()
C = self.SVMOM.CdoubleSpinBox.value()
max_iter = self.SVMOM.max_iterspinBox.value()
degree = self.SVMOM.degreespinBox.value()
verbose = self.SVMOM.verbosecheckBox.isChecked()
probability = self.SVMOM.probabilitycheckBox.isChecked()
shrinking = self.SVMOM.ShrinkingcheckBox.isChecked()
self.SVMValues = {
'kernel':[kernel],
'gamma':[gamma],
'decision_function_shape':[dfs],
'C':[C],
'max_iter':[max_iter],
'degree':[degree],
'verbose':[verbose],
'probability':[probability],
'shrinking':[shrinking]
}
self.SVMDM.accept()
def DTVal(self):
criterion = self.DTOM.criterionlist.currentText()
splitter = self.DTOM.splitterlist.currentText()
max_features = self.DTOM.max_featureslist.currentText()
min_samples_split = self.DTOM.min_samples_splitdoubleSpinBox.value()
max_depth = self.DTOM.max_depthspinBox.value()
min_samples_leaf = self.DTOM.min_samples_leafspinBox.value()
self.DTValues = {
'criterion':[criterion],
'splitter':[splitter],
'max_features':[max_features],
'min_samples_split':[min_samples_split],
'max_depth':[max_depth],
'min_samples_leaf':[min_samples_leaf]
}
self.DTDM.accept()
def KNNVal(self):
algorithm = self.KNNOM.algorithmlist.currentText()
weights = self.KNNOM.weightslist.currentText()
p = self.KNNOM.pspinBox.value()
leaf_size = self.KNNOM.leaf_sizespinBox.value()
n_neighbors = self.KNNOM.n_neighborsspinBox.value()
self.KNNValues = {
'algorithm':[algorithm],
'weights':[weights],
'p':[p],
'leaf_size':[leaf_size],
'n_neighbors':[n_neighbors]
}
self.KNNDM.accept()
def RTVal(self):
criterion = self.RTOM.criterionlist.currentText()
max_features = self.RTOM.max_featureslist.currentText()
min_samples_split = self.RTOM.min_samples_splitdoubleSpinBox.value()
max_depth = self.RTOM.max_depthspinBox.value()
n_estimators = self.RTOM.n_estimatorsspinBox.value()
warm_start = self.RTOM.warm_startcheckBox.isChecked()
oob_score = self.RTOM.oob_scorecheckBox.isChecked()
bootstrap = self.RTOM.bootstrapcheckBox.isChecked()
self.RTValues = {
'criterion':[criterion],
'max_features':[max_features],
'min_samples_split':[min_samples_split],
'max_depth':[max_depth],
'n_estimators':[n_estimators],
'warm_start':[warm_start],
'oob_score':[oob_score],
'bootstrap':[bootstrap]}
self.RTDM.accept()
def CHPTVal(self):
self.CHPTValues['SVM'] = self.CHPTOM.SVMValues
self.CHPTValues['DecisionTree'] = self.CHPTOM.DTValues
self.CHPTValues['KNearestNeighbours'] = self.CHPTOM.KNNValues
self.CHPTValues['RandomForest'] = self.CHPTOM.RTValues
self.CHPTDM.accept()
def HPTVal(self):
if self.HPTOM.LinearR.isChecked():
self.HPTValues['Linear Regression'] = True
else:
self.HPTValues['Linear Regression'] = False
if self.HPTOM.LogisticR.isChecked():
self.HPTValues['LogisticR'] = True
else:
self.HPTValues['LogisticR'] = False
self.HPTValues['Logistic Regression'] = self.HPTOM.LValues
self.HPTDM.accept()
def retranslateUi(self, MainWindow):
_translate = QtCore.QCoreApplication.translate
MainWindow.setWindowTitle(_translate("MainWindow", "Data Analysis"))
self.msg1.setText(_translate("MainWindow", "<html><head/><body><p><span style=\" font-size:14pt; color:#ffffff;\">DATA CLEANING</span></p></body></html>"))
self.DisplayData.setText(_translate("MainWindow", "Display Data"))
self.EditData.setItemText(0, _translate("MainWindow", "Modification"))
self.EditData.setItemText(1, _translate("MainWindow", "Delete Rows"))
self.EditData.setItemText(2, _translate("MainWindow", "One Hot Encode"))
self.DescribeDate.setText(_translate("MainWindow", "Describe Data"))
self.FeatureTuning.setText(_translate("MainWindow", "Feature Tuning"))
self.DropBox.setItemText(0, _translate("MainWindow", "Graphical View"))
self.DropBox.setItemText(1, _translate("MainWindow", "Histogram"))
self.DropBox.setItemText(2, _translate("MainWindow", "Correlation Data"))
self.msg2.setText(_translate("MainWindow", "<html><head/><body><p><span style=\" font-size:14pt; color:#ffffff;\">MODEL TRAINING</span></p></body></html>"))
self.ModelType.setItemText(0, _translate("MainWindow", "Select Problem Type"))
self.ModelType.setItemText(1, _translate("MainWindow", "Regression"))
self.ModelType.setItemText(2, _translate("MainWindow", "Classification"))
self.RegressionType.setItemText(0, _translate("MainWindow", "Regression Type"))
self.RegressionType.setItemText(1, _translate("MainWindow", "Linear Regression"))
self.RegressionType.setItemText(2, _translate("MainWindow", "Logistic Regression"))
self.RegressionType.setItemText(3, _translate("MainWindow", " Best Fit Score"))
self.ClassificationType.setItemText(0, _translate("MainWindow", "Classification Type"))
self.ClassificationType.setItemText(1, _translate("MainWindow", "SVM"))
self.ClassificationType.setItemText(2, _translate("MainWindow", "NaiveBayes"))
self.ClassificationType.setItemText(3, _translate("MainWindow", "DecisionTree"))
self.ClassificationType.setItemText(4, _translate("MainWindow", "RandomForest"))
self.ClassificationType.setItemText(5, _translate("MainWindow", "KNearestNeighbors"))
self.ClassificationType.setItemText(6, _translate("MainWindow", " Best Fit Score"))
self.ClassificationTypeNB.setItemText(0, _translate("MainWindow", "GaussianNB"))
self.ClassificationTypeNB.setItemText(1, _translate("MainWindow", "BernoulliNB"))
self.ClassificationTypeNB.setItemText(2, _translate("MainWindow", "MultinomialNB"))
self.Train.setText(_translate("MainWindow", "Train"))
self.menuFile.setTitle(_translate("MainWindow", "File"))
self.menuSave.setTitle(_translate("MainWindow", "Output"))
self.menuHelp.setTitle(_translate("MainWindow", "Help"))
self.actionData_Cleaning.setText(_translate("MainWindow", "Data Cleaning"))
self.actionModel_Training.setText(_translate("MainWindow", "Model Training"))
self.actionVersion.setText(_translate("MainWindow", "ClearAll"))
self.actionAbout.setText(_translate("MainWindow", "About"))
self.actionOpen.setText(_translate("MainWindow", "Open File"))
self.actionAbout_2.setText(_translate("MainWindow", "About Data Cleaning"))
self.actionAbout_Model_Traning.setText(_translate("MainWindow", "About Model Traning"))
self.actionAs_CSV.setText(_translate("MainWindow", "as CSV"))
self.actionAs_PDF.setText(_translate("MainWindow", "as PDF"))
self.actionExit.setText(_translate("MainWindow", "Exit"))
self.actionPredict.setText(_translate("MainWindow", "Predict"))
self.actionSave.setText(_translate("MainWindow", "Save"))
import Images_rc
if __name__ == "__main__":
import sys
app = QtWidgets.QApplication(sys.argv)
app.setStyle('Fusion')
MainWindow = QtWidgets.QMainWindow()
ui = Ui_MainWindow()
ui.setupUi(MainWindow)
MainWindow.show()
sys.exit(app.exec_())