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Functions228 in github.com/GitsSaikat/PyGen

⨍ Functions 228◇ Types & classes 41
Methodhandle_imbalanced_data
Handle imbalanced datasets using SMOTE
examples_package/AutoML_package_20241024075050/AutoML/DataPreprocessing.py:45
Methodhandle_missing_values
(self, data)
examples_package/AutoML_package_20241024075050/AutoML/DataPreprocessing.py:14
Methodlemmatize_text
Lemmatization with POS tagging
examples_package/AutoSpeech_package_20241024085908/AutoSpeech/natural_language_processing.py:47
Methodload_audiofile
Securely load and validate audio file
examples_package/AutoSpeech_package_20241024085908/AutoSpeech/audiospeech_preprocessing.py:15
Methodload_image
Load and validate image
examples_package/AutoVision_package_20241024085344/AutoVision/main.py:27
Methodload_pipeline
Load a saved pipeline
examples_package/AutoML_package_20241024075050/AutoML/AutoML.py:76
Methodoptimize_pipeline
Optimize pipeline using grid search
examples_package/AutoML_package_20241024075050/AutoML/AutoML.py:50
Functionpairwise_agreement
(row)
pygen/stests.py:56
Methodperform_hyperparameter_tuning
(self, model, hyperparameter_space)
examples_package/AutoML_package_20241024075050/AutoML/AutomateModelSelectionAndHyperparameterTuning.py:41
Methodplot_confusion_matrix
Plot confusion matrix using seaborn
examples_package/AutoML_package_20241024075050/AutoML/PerformanceEvaluation.py:53
Methodplot_feature_importance_chart
Plot feature importance chart
examples_package/AutoML_package_20241024075050/AutoML/ExplainabilityAndInterpretability.py:92
Methodplot_pdp_interaction
Plot partial dependence interaction between two features
examples_package/AutoML_package_20241024075050/AutoML/ExplainabilityAndInterpretability.py:111
Methodplot_roc_curve
Plot ROC curve and calculate AUC
examples_package/AutoML_package_20241024075050/AutoML/PerformanceEvaluation.py:37
Methodpreprocess
(self, data: pd.DataFrame)
data/AutoML/reference_code.py:36
Methodremove_outliers
(self, data, outliers)
examples_package/AutoML_package_20241024075050/AutoML/DataPreprocessing.py:40
Methodrobust_scaling
Scale data using RobustScaler for handling outliers
examples_package/AutoML_package_20241024075050/AutoML/DataPreprocessing.py:60
Methodrun_loop
(self)
examples_package/AutoSpeech_package_20241024085908/AutoSpeech/speech_recognition.py:159
Methodsave_model
Save trained model
data/AutoVison/context_code.py:105
Methodsave_model
Save trained model
examples_package/AutoVision_package_20241024085344/AutoVision/main.py:104
Methodsave_pipeline
Save the pipeline to disk
examples_package/AutoML_package_20241024075050/AutoML/AutoML.py:72
Methodscale_and_normalize
(self, data)
examples_package/AutoML_package_20241024075050/AutoML/DataPreprocessing.py:25
Methodselect_best_model
(self, X_train: np.ndarray, y_train: np.ndarray, X_val: np.ndarray, y_val: np.ndarray
data/AutoML/reference_code.py:91
Methodstabilizer_code
(self)
examples_package/Quantum Error Correction_package_20241024080522/Quantum Error Detection and Correction/main.py:19
Methodsyndrome_measurement
(self, state: np.ndarray)
examples_package/Quantum Error Correction_package_20241024080522/Quantum Error Detection and Correction/main.py:30
Methodtrain
Train the model with extracted features
data/AutoVison/context_code.py:50
Methodtrain
Train the model with extracted features
examples_package/AutoVision_package_20241024085344/AutoVision/main.py:49
Methodtraining_loop
(self)
examples_package/AutoSpeech_package_20241024085908/AutoSpeech/speech_recognition.py:77
Methodtune_hyperparameters
(self, model: BaseEstimator, X_train: np.ndarray, y_train: np.ndarray)
data/AutoML/reference_code.py:107
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