Jupyter Notebook presentation for class imbalance in binary classification
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Aug 11, 2018 - Jupyter Notebook
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imbalanced-data
Here are 17 public repositories matching this topic...
Data Science Classification General Notebook
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Jul 22, 2023 - Jupyter Notebook
Credit card fraud detection, gender classification from name etc.
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Oct 6, 2020 - Jupyter Notebook
My kernels on Kaggle
machine-learning deep-learning time-series regression eda classification imbalanced-data pycaret fastautoml
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Jul 30, 2022
Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies
visualization data-science machine-learning exploratory-data-analysis cross-validation regression feature-selection classification recall outlier-detection feature-engineering precision imbalanced-data f1-score sklearn-library
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May 28, 2024 - Jupyter Notebook
Proposed assignment notebooks for Advanced Topics in Machine Learning tasks
machine-learning numpy scikit-learn multi-label-classification active-learning imbalanced-data cost-sensitive-learning multi-instance-learning
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Jul 6, 2022 - Jupyter Notebook
Machine learning notebooks
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Apr 8, 2020 - Jupyter Notebook
This notebook tries to make fraud/not fraud predictions on a transactions dataset with highly imbalanced data.
machine-learning xgboost classification imbalanced-data smote fraud-detection fraudulent-transactions oversampling-technique
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Mar 14, 2022 - Jupyter Notebook
A Jupyter notebook that applies machine learning techniques to detect credit card fraud on imbalanced data. It covers data preprocessing, EDA, handling class imbalance, training classifiers (Logistic Regression, Decision Tree, RandomForest), and saving the trained models.
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Sep 13, 2024 - Jupyter Notebook
This particular notebook consist of all the Feature Engineering technique and Feature Transformation technique
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Jul 5, 2022 - Jupyter Notebook
This notebook will walk you through the steps for dealing with an imbalanced dataset using an example of a real project that I recently completed.
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Mar 8, 2022 - Jupyter Notebook
This repo has a notebook that I worked on for making a fraud detection model. The dataset was Highly imbalanced, so i used random undersampling to balance the data.
machine-learning python3 imbalanced-data fraud-detection classification-model fraudulent-transactions
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Apr 10, 2022 - Jupyter Notebook
This notebook shows how the f1 metric differs accuracy on imbalanced data. The heart disease dataset from kaggle is used (https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease).
comparison accuracy logistic-regression imbalanced-data f1-score accuracy-metrics f1score imbalance-classification
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Apr 8, 2022 - Jupyter Notebook
Contained in this repository are the Jupyter notebooks that contain the scripts used in this project. Examples include: exploratory data analysis, creation of training, validation and test data sets, and CNN model development and data extraction.
data binary fog cnn computer vision meteorology classification transfer-learning evaluation-metrics augmentation imbalanced-data imbalance-classification
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Jul 7, 2021 - Jupyter Notebook
This project analyzes phone usage patterns in India and predicts the primary use of mobile devices based on various features. The notebook covers data preprocessing, exploratory data analysis (EDA), and model training using multiple classification algorithms.
random-forest numpy scikit-learn exploratory-data-analysis jupyter-notebook pandas seaborn xgboost lightgbm logistic-regression matplotlib confusion-matrix adaboost imbalanced-data classification-report gradient-boosting datavisualization datapreprocessing accuracy-score supportvectormachines
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Feb 14, 2025 - Jupyter Notebook
In this notebook, I applied statistical methods for imbalanced data analysis. In terms of basics, it starts with null check, data description and handling missing values. There exists right skewness in data for numerical columns. Shapiro-Wilk and Anderson darling tests are applied to prove that data is not distributed normally. Outlier detection…
statistics analysis data-analysis outlier-detection imbalanced-data chi-square-test shapiro-wilk anderson-darling-test
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Dec 19, 2021 - Jupyter Notebook
Detect Fraud Transaction from the dataset . The project involves dealing with unbalanced dataset and concept drift. I have implemented 4 machine learning algorithms to predict Fraud Transaction . These are - Logistic Regression ,Support Vector Machine(SVM), Local Outlier Factor(LOF) and isolation Tree.See my python 3 notebook to get more insight…
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Jun 8, 2020 - Jupyter Notebook
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