added random state to split in function
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3 changed files with 24 additions and 21 deletions
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@ -174,29 +174,29 @@ def CMLogoSkf(cm_input_df
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, '\nTEST Target dim:', cm_bts_y.shape)
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print("Running Multiple models on LOGO with SKF")
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# #%%:Running Multiple models on LOGO with SKF
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# cD3_v2 = MultModelsCl_logo_skf(input_df = cm_X
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# , target = cm_y
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# #, group = 'none'
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# , sel_cv = skf_cv
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#%%:Running Multiple models on LOGO with SKF
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cD3_v2 = MultModelsCl_logo_skf(input_df = cm_X
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, target = cm_y
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#, group = 'none'
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, sel_cv = skf_cv
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# , blind_test_df = cm_bts_X
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# , blind_test_target = cm_bts_y
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, blind_test_df = cm_bts_X
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, blind_test_target = cm_bts_y
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# , tts_split_type = tts_split_type
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, tts_split_type = tts_split_type
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# , resampling_type = 'none' # default
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# , add_cm = True
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# , add_yn = True
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# , var_type = 'mixed'
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, resampling_type = 'none' # default
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, add_cm = True
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, add_yn = True
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, var_type = 'mixed'
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# , run_blind_test = True
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# , return_formatted_output = True
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# , random_state = 42
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# , n_jobs = os.cpu_count() # the number of jobs should equal the number of CPU cores
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# )
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, run_blind_test = True
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, return_formatted_output = True
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, random_state = 42
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, n_jobs = os.cpu_count() # the number of jobs should equal the number of CPU cores
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)
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# cD3_v2.to_csv(outFile)
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cD3_v2.to_csv(outFile)
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#%% RUN
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#===============
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@ -215,7 +215,7 @@ def MultModelsCl(input_df, target, skf_cv
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, ('Naive Bayes' , BernoulliNB() )
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, ('Passive Aggresive' , PassiveAggressiveClassifier(**rs, **njobs) )
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, ('QDA' , QuadraticDiscriminantAnalysis() )
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, ('Random Forest' , RandomForestClassifier(**rs, n_estimators = 1000 ) )
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, ('Random Forest' , RandomForestClassifier(**rs, n_estimators = 1000, **njobs ) )
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, ('Random Forest2' , RandomForestClassifier(min_samples_leaf = 5
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, n_estimators = 1000
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, bootstrap = True
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@ -40,7 +40,7 @@ import argparse
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import re
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homedir = os.path.expanduser("~")
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#%% GLOBALS
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rs = {'random_state': 42}
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#rs = {'random_state': 42}
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njobs = {'n_jobs': os.cpu_count() } # the number of jobs should equal the number of CPU cores
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#%% Define split_tts function #################################################
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@ -51,7 +51,10 @@ def split_tts(ml_input_data
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, dst_colname = 'dst'# determine how to subset the actual vs reverse data
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, target_colname = 'dst_mode'
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, include_gene_name = True
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, k_smote = 5):
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, k_smote = 5
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, random_state = 42):
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rs = {'random_state': random_state}
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outDict = {}
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