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065de4c5e8
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56236d755f
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@ -361,8 +361,7 @@ class eNoseTrainer:
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plt.close()
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plt.close()
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def fit(self):
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def fit(self):
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windows = [128,]
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windows = [128, 256, 384]
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# windows = [128, 256, 384]
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total_train_queue = 2*int(1/self.ratio)*(len(self.get_model_train())+len(windows))
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total_train_queue = 2*int(1/self.ratio)*(len(self.get_model_train())+len(windows))
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self.logger.info("{:=^60}".format(f'Begin Fit {total_train_queue} Models'))
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self.logger.info("{:=^60}".format(f'Begin Fit {total_train_queue} Models'))
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self.trained = 0
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self.trained = 0
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@ -13,7 +13,7 @@ fi
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env_name=$1
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env_name=$1
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conda create -n "$env_name" python scikit-learn==1.3.1 xgboost conda-forge::tensorflow-cpu conda-forge::optuna keras pandas numpy matplotlib openpyxl xlsxwriter conda-forge::enlighten
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conda create -n "$env_name" python scikit-learn==1.3.1 xgboost conda-forge::tensorflow-cpu conda-forge::ray-tune keras pandas numpy matplotlib openpyxl xlsxwriter conda-forge::enlighten
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if [ $? -eq 0 ]; then
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if [ $? -eq 0 ]; then
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echo "Packages installed successfully in environment '$env_name'"
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echo "Packages installed successfully in environment '$env_name'"
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else
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else
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