an R project of manipulating and fittingdata into regression with 95.5% R-Square, involving Automated Selection, detecting outliers, influential observations and multicollinearity
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Updated
Oct 12, 2018
an R project of manipulating and fittingdata into regression with 95.5% R-Square, involving Automated Selection, detecting outliers, influential observations and multicollinearity
Predicting Customer Response to Telemarketing Campaigns for Term Deposit. Output variable Whether the client has subscribed a term deposit or not.
This lab focuses on image transformation techniques in OpenCV with Python. Tasks include creating mirror images using both Affine and Projective transformations, applying a Log Transformer for contrast adjustment, and implementing a Power-Law Transformer for gamma correction.
Predict delivery time using sorting time and Build a prediction model for salary hike.
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.
Introdução a técnicas de modelagem de dados para modelos de Regressão Linear utilizando StatsModels e Scikit Learn.
Spatial Data Science
Data Science - Simple Linear Regression Work
Data prepration and preprocessing for predictive modeling with SAS and Python
Prediction model for hourly bicycle utilization - task assignment
Detects sufficient and necessary conditions for pattern inversion conditional on log transform
Digital Image Processing (Java)
Analysis of Skewness and Kurtosis in Stock Return data and their Transformations
Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
Feature engineering is the process of transforming raw data into features. Here are some basic ideas about feature engineering.
Building a prediction model for Salary hike using Years of Experience
Simple Linear Regression
Modeling King County Home Prices via Multiple Linear Regression
Data Set: House Prices: Advanced Regression Techniques Feature Engineering with 80+ Features
Image Processing Algorithms
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