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recall-value

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Ninad077 / Machine_Learning-Logistic_Regression

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Content: Machine Learning, Logistic regression steps, Probability matrix, Confusion matrix, Accuracy score, Recall value, Data preprocessing, Label encoding, Scaling the data, Splitting train test data, Running Logistic Regression, Y prediction on test data, Class imbalance, Type 1 & Type 2 errors.

machine-learning confusion-matrix data-preprocessing class-imbalance label-encoding accuracy-score probability-matrix recall-value scaling-the-data splitting-train-test-data y-prediction-on-test-data type-1-and-type-2-errors
  • Updated May 6, 2024
  • Jupyter Notebook

Ninad077 / Machine_Learning-KNN_algorithm

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Content: Machine Learning, KNN concept, Euclidean distance, Data preprocessing, Scaling the data, Performing train-test split, Applying KNeighbors Classifier, Predicting Y_pred based on X_test, Evaluation using Confusion Matrix, Accuracy score, Recall value & Precision, Underfitting & Overfitting, Measures to overcome Underfitting & Overfitting

machine-learning data-preprocessing precision euclidean-distance accuracy-score recall-value scaling-the-data knn-concept underfitting-and-overfitting performing-train-test-split applying-k-neighbors-classifier predicting-y-based-on-test-data evaluation-using-confusion-matrix measures-to-overcome-underfitting-and-overfitting
  • Updated May 6, 2024
  • Jupyter Notebook

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