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log-transformation

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sharmaroshan / Predicting_Money_Spent_at_Resort

Star 7

It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.

tutorial machine regression eda data-visualization seaborn lasso xgboost scipy predictive-modeling palettes stacking elastic-net boosting log-transformation kernel-ridge ensembling box-cox lgboost robust-scaling
  • Updated May 13, 2019
  • Jupyter Notebook

abalmumcu / .pgm-file-read-manipulation-write

Star 2

This repo includes; Image Negative, Logarithmic Transformation, Power-Law (Gamma) Transformation, Averaging Filter, Median Filter, Laplacian Filter, Sobel Gradiant, Histogram Equalization, DFT, Marr and Hildreth, Otsu Thresholding, Global thresholding

dft pgm median-filter laplacian histogram-equalization averaging-filter sobel-gradient log-transformation otsu-threshold marr-hildreth gamma-transformation image-negative pgm-extension global-threshold
  • Updated May 22, 2023
  • C++

aneeshmurali-n / ML_Bangalore_House_Price_Analysis

Star 1

This project focusing on statistical analysis to understand and prepare data for potential machine learning applications. The dataset house_price.csv includes property prices in Bangalore. The analysis aims to perform exploratory data analysis (EDA), detect and handle outliers, check data distribution and normality, and analyze correlations.

python correlation numpy heatmap exploratory-data-analysis data-transformation pandas seaborn scipy scatter-plot matplotlib outlier-detection box-plot log-transformation data-distribution iqr-method percentile-method histplot outlier-handling z-score-method
  • Updated Aug 28, 2024
  • Jupyter Notebook

shanuhalli / Assignment-Neural-Networks

Star 1

Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.

machine-learning deep-learning neural-network tensorflow keras optimizer feature-selection outlier-detection confusion-matrix feature-engineering hyperparameter-tuning log-transformation label-encoder sklearn-metrics roc-auc-curve standard-scaler assignment-16
  • Updated Feb 8, 2023
  • Jupyter Notebook

MamiyaA / FeatureFinder

Star 1

Jupyter notebook and "Streamlit" python scripts for identifying features that can predict employee turn over rates at 250 senior care centers across the US. Combines multiple repetition of Lasso regression and linear regression. Integrates U.S. census data, employee salary, and employee tenure with data on employee satisfaction and engagement to…

linear-regression exploratory-data-analysis standardization preprocessing census-data lasso-regression regression-analysis log-transformation
  • Updated Oct 9, 2020
  • Jupyter Notebook

lovpatel93 / Udacity-Finding_Donors_for_Charity_ML

Star 1

Udacity Data Scientist Nanodegree Project - Employ supervised algorithms to accurately model individuals income

data-visualization feature-selection confusion-matrix adaboost data-exploration evaluation-metrics svm-classifier normalization supervised-learning-algorithms feature-importance model-tuning gridsearchcv ensemble-models log-transformation naive-predictor decison-trees svc-svm
  • Updated Feb 21, 2019
  • Jupyter Notebook

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