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This repository shares the code for performing cluster analysis and machine learing algorithms intended to identify subtypes within the Crowe I DDH cases.
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For each analysis, please read the instructions along the code to reproduce this analysis.
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## raw data ##
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Raw data contains data for each case that was inlcuded in the cluster analysis and in the development of machine learning algorithms. Note that the average of four measurements was shown in raw data.
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## data_for_develop_ML_algorithms ##
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Raw_data for developing ML algorithms to predict the classification of new cases
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## data_for_external_validation ##
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Raw data for external validation for ML algorithms
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## Code_Cluster ##
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Code and instruction to perform cluster analysis
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## Code_ANN ##
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Code and instruction to develop ANN algorithm for new case prediction, and use external data to test the algorithm.
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## Code_Decisiontree ##
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Code and instruction to develop Decisiontree algorithm for new case prediction, and use external data to test the algorithm.
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## Code_K-NN ##
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Code and instruction to develop K-NN algorithm for new case prediction, and use external data to test the algorithm.
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## Code_logisticregression ##
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Code and instruction to develop logisticregression algorithm for new case prediction, and use external data to test the algorithm.
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## Code_Randomforest ##
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Code and instruction to develop random forest algorithm for new case prediction, and use external data to test the algorithm.
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## Code_SVM ##
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Code and instruction to develop SVM algorithm for new case prediction, and use external data to test the algorithm.
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