From 901371de2ce0c57da29c130562bebd5e76d78d56 Mon Sep 17 00:00:00 2001 From: Joaquin Torres Bravo Date: Thu, 9 May 2024 16:33:31 +0200 Subject: [PATCH] tuning post --- model_selection/hyperparam_tuning.py | 13 ++++++------- model_selection/output/hyperparam_post.xlsx | Bin 0 -> 7993 bytes 2 files changed, 6 insertions(+), 7 deletions(-) create mode 100644 model_selection/output/hyperparam_post.xlsx diff --git a/model_selection/hyperparam_tuning.py b/model_selection/hyperparam_tuning.py index e688b7c..22d004a 100644 --- a/model_selection/hyperparam_tuning.py +++ b/model_selection/hyperparam_tuning.py @@ -142,18 +142,17 @@ if __name__ == "__main__": # -------------------------------------------------------------------------------------------------------- # Store each df as a sheet in an excel file sheets_dict = {} - for i, group in enumerate(['pre']): - for j, method in enumerate(['under_']): #['', '', 'over_', 'under_'] + for i, group in enumerate(['post']): + for j, method in enumerate(['', '', 'over_', 'under_']): # Get dataset based on group and method X = data_dic['X_train_' + method + group] y = data_dic['y_train_' + method + group] # Use group of models with class weight if needed - # models = models_CS if j == 2 else models_simple - models = models_simple + models = models_CS if j == 2 else models_simple # Save results: params and best score for each of the mdodels of this method and group hyperparam_df = pd.DataFrame(index=list(models.keys()), columns=['Parameters','Score']) for model_name, model in models.items(): - print(f"{group}-{method_names[3]}-{model_name}") + print(f"{group}-{method_names[j]}-{model_name}") # Find optimal hyperparams for curr model params = hyperparameters[model_name] search = RandomizedSearchCV(model, param_distributions=params, cv=cv, n_jobs=8, scoring='precision') @@ -162,11 +161,11 @@ if __name__ == "__main__": hyperparam_df.at[model_name,'Score']=round(search.best_score_,4) # Store the DataFrame in the dictionary with a unique key for each sheet - sheet_name = f"{group}_{method_names[3]}" + sheet_name = f"{group}_{method_names[j]}" sheets_dict[sheet_name] = hyperparam_df # Write results to Excel file - with pd.ExcelWriter('./output/hyperparam_pre_UNDER.xlsx') as writer: + with pd.ExcelWriter('./output/hyperparam_post.xlsx') as writer: for sheet_name, data in sheets_dict.items(): data.to_excel(writer, sheet_name=sheet_name) diff --git a/model_selection/output/hyperparam_post.xlsx b/model_selection/output/hyperparam_post.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..848361b289ff6bd08da83976326ce8e72a6ad4b8 GIT binary patch literal 7993 zcmaKR1yo$w5^duiq#-zg;O_1Ox8T8o6WrZ3NN^4A4#C}BgS!QS6Wkgnzmxp;<_&-5 zcdx#^?pj^D>z-4!cbzH)87OE>0000F00tJTi)(fv`-AVQz#la5$H>M|!QRH!fl=Sq zmciA^QZ7;sshbH+^r!Uxs^>P$ zd*fdY=f}vs?O{R=`Z+w~aZpPLpHqfikS-)*fDxh<@2Vwwk=F^S|A$u&HdVS`>w zULu)3=8itc2g-c48WzufXAD!Ag&Z*ngyEb(BpDp5y9Ryf57lo!6f~F9HoI>GMM%4P zxO*lijz`FlrFWO1YuaHc#zu|0Dsq9o_`VXeOL=@R)P_T0%LA)zyt`HBt!~4qpter-R1`7bBQ33!!@XEMa zGCG~y+y|5xt0dTZ|m<^$k2tE za0@F=I}!6`b?P+D06kn@LqLq475^}J8CT4aIqh{VJVw&FAGOP?YJp~!**FqLdR{to zra}`cikddM#I@V6SZ}aKR3eOXA%O3MDVjoR&u=aJ9+tid7?1Ds5VH7LGvTWf`;6HX zZpmwgd{^o2?KC$LRI?bEoRakQAM%QaX_f-zPGiBdpz!jftB*N*f_jfK!-tm~*{tx^ zH_u$T>PM!+Yzd&(67{m^&2xslN|;&TI-dkxkq_JsRc(fU|c}R>8AExc<|6ckGmQ z^xQagodOlfwTlTU}}?@CHpBZzIiN$6?a)9xh*e5~SL?lKWX53*s}*8e0iFUEiE* zLg(3+G(JKg#%MeetZ>k0G75}hZf`kB;1g~B(o@>B&}lp)*`0JulvxdFp(DlU9xGm# zcm=*wu;~<^`xDG<8apCE3_c;G34V<@NuXKFDNzMkWXhLrbXpMs16&R~`?{BY^>)R9 zdYTyhldkepwdfBTW$bYRdV`0fF-~K1F)z?#bvVJl9Se&_?;r}|l1@3wu~UbB%+TqP z>e}-k`S9529W={oNf&u7F@r6=g-THo>>yiCQwAgf(UcgL?p27 z?uy8n*x#y9?(YHdb8?BZyY$AtliP>EYdrs?>5@Nts)3W#%cN^MOzWGtwN~$aIrGvy z8v~W$JNwbW0hNk4>ILr1&cjDjfsC`GyG63ViWCic(wEUPel@~mjSpeNr!>6?dq!I1 z2qP-f#+;upGDPsL_m!`t6Xv%ony4E2w6^vuvKkfspeYlH=^4r173N!EPS9NhS&X3T&8G zmStpg;thI@^JjFJ>qdI?S#SXrije0@s(Q>?{ZO>gIi9lNVtcl`pS5*2Cu2943ykZm zE2v#?tzIi}cbg>vO-hHq8CP|w5{|2ComaM-^Ved@k3VUA8O%gRmw$69`~m zVzX>19LGk(0wG4@heS^y{f!C;e3R~w+Rl-isIkVr2ypv|(FFv_>r9bjV1BAZh9SYW z-#j^qGj|D}zoYZB3RGb+n#CS|6WYbkYX4?Ih5Vv?i2~{4@`lQ23tl^go=lIsbvixe z&t;t%{#tB)@r&H#b)uSJhgA2*Zn3hT>T^W5ENk4h%RJwpbasGrZ}Pmmygq&MMK3jI zZ?1TIOPv85socb`goCjK6NA{d4)yy}dMHiHT^L!NxYZ$I|$)+2HY4D|>>P!C; 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