added notes to run yc models with dissected features
This commit is contained in:
parent
a784f9cc4e
commit
f761dd4479
2 changed files with 13 additions and 98 deletions
|
|
@ -1,3 +1,10 @@
|
||||||
|
#!/usr/bin/env python3
|
||||||
|
# -*- coding: utf-8 -*-
|
||||||
|
"""
|
||||||
|
Created on Sun May 29 07:43:21 2022
|
||||||
|
|
||||||
|
@author: tanu
|
||||||
|
"""
|
||||||
import pandas as pd
|
import pandas as pd
|
||||||
import numpy as np
|
import numpy as np
|
||||||
import scipy as sp
|
import scipy as sp
|
||||||
|
|
@ -251,100 +258,4 @@ def run_all_ML(input_pd, target_label, blind_test_input_df, blind_test_target, p
|
||||||
|
|
||||||
#return(result_pd)
|
#return(result_pd)
|
||||||
return(results_all)
|
return(results_all)
|
||||||
|
|
||||||
|
|
||||||
#%% CALL function
|
|
||||||
#run_all_ML(input_pd=X, target_label=y, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
# Baseline_data
|
|
||||||
|
|
||||||
YC_resD2 = run_all_ML(input_pd=X, target_label=y, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
CVResultsDF_baseline = YC_resD2['CrossValResultsDF']
|
|
||||||
CVResultsDF_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
BTSResultsDF_baseline = YC_resD2['BlindTestResultsDF']
|
|
||||||
BTSResultsDF_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# from sklearn.utils import all_estimators
|
|
||||||
# for name, algorithm in all_estimators(type_filter="classifier"):
|
|
||||||
# clf = algorithm()
|
|
||||||
# print('Name:', name, '\nAlgo:', clf)
|
|
||||||
|
|
||||||
# Random Oversampling
|
|
||||||
YC_resD_ros = run_all_ML(input_pd=X_ros, target_label=y_ros, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
CVResultsDF_ros = YC_resD_ros['CrossValResultsDF']
|
|
||||||
CVResultsDF_ros.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
BTSResultsDF_ros = YC_resD_ros['BlindTestResultsDF']
|
|
||||||
BTSResultsDF_ros.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# Random Undersampling
|
|
||||||
YC_resD_rus = run_all_ML(input_pd=X_rus, target_label=y_rus, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
CVResultsDF_rus = YC_resD_rus['CrossValResultsDF']
|
|
||||||
CVResultsDF_rus.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
BTSResultsDF_rus = YC_resD_rus['BlindTestResultsDF']
|
|
||||||
BTSResultsDF_rus.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# Random Oversampling+Undersampling
|
|
||||||
YC_resD_rouC = run_all_ML(input_pd=X_rouC, target_label=y_rouC, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
CVResultsDF_rouC = YC_resD_rouC['CrossValResultsDF']
|
|
||||||
CVResultsDF_rouC.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
BTSResultsDF_rouC = YC_resD_rouC['BlindTestResultsDF']
|
|
||||||
BTSResultsDF_rouC.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# SMOTE NC
|
|
||||||
YC_resD_smnc = run_all_ML(input_pd=X_smnc, target_label=y_smnc, blind_test_input_df=X_bts, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
CVResultsDF_smnc = YC_resD_smnc['CrossValResultsDF']
|
|
||||||
CVResultsDF_smnc.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
BTSResultsDF_smnc = YC_resD_smnc['BlindTestResultsDF']
|
|
||||||
BTSResultsDF_smnc.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
##############################################################################
|
|
||||||
#============================================
|
|
||||||
# BASELINE models with dissected featues
|
|
||||||
#============================================
|
|
||||||
# Genomics
|
|
||||||
yC_gf = run_all_ML(input_pd=X[X_genomicFN], target_label=y, blind_test_input_df=X_bts[X_genomicFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_gfCT_baseline= yC_gf['CrossValResultsDF']
|
|
||||||
yc_gfCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_gfBT_baseline = yC_gf['BlindTestResultsDF']
|
|
||||||
yc_gfBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# Evolutionary
|
|
||||||
yC_ev = run_all_ML(input_pd=X[X_evolFN], target_label=y, blind_test_input_df=X_bts[X_evolFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_evCT_baseline= yC_ev['CrossValResultsDF']
|
|
||||||
yc_evCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_evBT_baseline = yC_ev['BlindTestResultsDF']
|
|
||||||
yc_evBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# strucF:All
|
|
||||||
yC_sfall = run_all_ML(input_pd=X[X_strFN], target_label=y, blind_test_input_df=X_bts[X_strFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_sfallCT_baseline= yC_sfall['CrossValResultsDF']
|
|
||||||
yc_sfallCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_sfallBT_baseline = yC_sfall['BlindTestResultsDF']
|
|
||||||
yc_sfallBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# strucF:Common ONLY
|
|
||||||
yC_sfco= run_all_ML(input_pd=X[common_cols_stabiltyN], target_label=y
|
|
||||||
, blind_test_input_df=X_bts[common_cols_stabiltyN]
|
|
||||||
, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_sfcoCT_baseline= yC_sfco['CrossValResultsDF']
|
|
||||||
yc_sfcoCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_sfcoBT_baseline = yC_sfco['BlindTestResultsDF']
|
|
||||||
yc_sfcoBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# strucF:common_stability + foldX_cols i.e interaction
|
|
||||||
yC_fxss= run_all_ML(input_pd=X[common_cols_stabiltyN+foldX_cols], target_label=y
|
|
||||||
, blind_test_input_df=X_bts[common_cols_stabiltyN+foldX_cols]
|
|
||||||
, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_fxssCT_baseline= yC_fxss['CrossValResultsDF']
|
|
||||||
yc_fxssCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_fxssBT_baseline = yC_fxss['BlindTestResultsDF']
|
|
||||||
yc_fxssBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
# categorical
|
|
||||||
yC_cat= run_all_ML(input_pd=X[categorical_FN], target_label=y
|
|
||||||
, blind_test_input_df=X_bts[categorical_FN]
|
|
||||||
, blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
|
|
||||||
yc_catCT_baseline= yC_cat['CrossValResultsDF']
|
|
||||||
yc_catCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
yc_catBT_baseline = yC_cat['BlindTestResultsDF']
|
|
||||||
yc_catBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
|
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -12,7 +12,6 @@ gene = 'pncA'
|
||||||
drug = 'pyrazinamide'
|
drug = 'pyrazinamide'
|
||||||
#total_mtblineage_u = 8
|
#total_mtblineage_u = 8
|
||||||
|
|
||||||
|
|
||||||
homedir = os.path.expanduser("~")
|
homedir = os.path.expanduser("~")
|
||||||
os.chdir( homedir + '/git/ML_AI_training/')
|
os.chdir( homedir + '/git/ML_AI_training/')
|
||||||
|
|
||||||
|
|
@ -21,8 +20,13 @@ setvars(gene,drug)
|
||||||
from UQ_ML_data import *
|
from UQ_ML_data import *
|
||||||
|
|
||||||
# from YC run_all_ML: run locally
|
# from YC run_all_ML: run locally
|
||||||
|
from UQ_yc_RunAllClfs import run_all_ML
|
||||||
|
|
||||||
|
# TT run all ML clfs: baseline mode
|
||||||
from UQ_MultModelsCl import MultModelsCl
|
from UQ_MultModelsCl import MultModelsCl
|
||||||
|
|
||||||
|
#%%###########################################################################
|
||||||
|
|
||||||
print('\n#####################################################################\n')
|
print('\n#####################################################################\n')
|
||||||
print('TESTING cmd:'
|
print('TESTING cmd:'
|
||||||
, '\nGene name:', gene
|
, '\nGene name:', gene
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue