Topic: log-transformation Goto Github
Some thing interesting about log-transformation
Some thing interesting about log-transformation
log-transformation,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
User: abalmumcu
log-transformation,Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand
User: adityashrm21
log-transformation,Data prepration and preprocessing for predictive modeling with SAS and Python
User: ajmalsarwary
log-transformation,Detects sufficient and necessary conditions for pattern inversion conditional on log transform
User: bencardoen
log-transformation,Prediction model for hourly bicycle utilization - task assignment
User: cesarliz10
log-transformation,Analysis of Skewness and Kurtosis in Stock Return data and their Transformations
User: dagocodes
log-transformation,In this project, I utilized the RFM Model on the WonderfulWines dataset. As a noteworthy enhancement, I employed a log transformation to achieve greater data symmetry, which ultimately resulted in more accurate outcomes.
User: emrecanduran
log-transformation,Image Processing Algorithms implemented from scratch with in-built concurrency support <3
User: itzmeanjan
Home Page: https://itzmeanjan.github.io/filterIt/
log-transformation,implement the concepts of Fourier Transformation technique such One-Dimensional Fourier Transform, Two-Dimensional Fourier Transform and Image Enhancement technique such as Image Inverse, Power Law Transformation and Log Transformation.
User: karthikeyana
log-transformation,Udacity Data Scientist Nanodegree Project - Employ supervised algorithms to accurately model individuals income
User: lovpatel93
Home Page: https://archive.ics.uci.edu/ml/datasets/Census+Income
log-transformation,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 improve the prediction accuracy and stability of the model.
User: mamiyaa
log-transformation,Image Processing Algorithms
User: mananpatel06
log-transformation,Data Set: House Prices: Advanced Regression Techniques Feature Engineering with 80+ Features
User: moindalvs
log-transformation,Learn about Simple Linear Regression for Data Science
User: moindalvs
log-transformation,Predicting Delivery Time Using Sorting Time
User: moindalvs
log-transformation,Building a prediction model for Salary hike using Years of Experience
User: moindalvs
log-transformation,It is a classification Problem where we are supposed to predict whether a loan would be approved or not.
User: pradnya1208
log-transformation,Data Science - Simple Linear Regression Work
User: saikrishnabudi
log-transformation,Image Enhancement( Unsharp masking, Histogram Equalisation)
User: sanjumaramattam
log-transformation,This repository introduces reader to basic concepts of simple linear regression and its application.
User: sanketmaneds
log-transformation,Digital Image Processing (Java)
User: sanvelkarthick
log-transformation,Image processing codes written in python
User: shahir-abdullah
log-transformation,Simple Linear Regression
User: shaikriyazsandy
log-transformation,Predicting Customer Response to Telemarketing Campaigns for Term Deposit. Output variable Whether the client has subscribed a term deposit or not.
User: shanuhalli
log-transformation,Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.
User: shanuhalli
log-transformation,Predict delivery time using sorting time and Build a prediction model for salary hike.
User: shanuhalli
log-transformation,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.
User: sharmaroshan
log-transformation,Introdução a técnicas de modelagem de dados para modelos de Regressão Linear utilizando StatsModels e Scikit Learn.
User: sidney-neto
log-transformation,Spatial Data Science
User: sreyadhar
log-transformation,an R project of manipulating and fittingdata into regression with 95.5% R-Square, involving Automated Selection, detecting outliers, influential observations and multicollinearity
User: ss2cp
log-transformation,Various things, operation related to digital Image Processing
User: susantabiswas
log-transformation,Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
User: sushantdhumak
log-transformation,Feature engineering is the process of transforming raw data into features. Here are some basic ideas about feature engineering.
User: towhid1
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