+65 61000 263
Contact@COE-Partners.com
Newsletter
Get a Quote

Predictive Modelling Using R

Predictive Modelling Using R

Welcome to our comprehensive guide on predictive modelling! This webpage is dedicated to providing an in-depth exploration of various modelling techniques utilised in both supervised and unsupervised machine learning. Here, you’ll find meticulously crafted code and output examples designed to showcase the power and versatility of these techniques.

Whether you’re a seasoned data scientist or just beginning your journey into the world of machine learning, our resources are tailored to enhance your understanding and practical skills. Dive in and discover how predictive modelling can transform data into actionable insights, driving innovation and informed decision-making in your field.

Data Preparation

Data preparation includes

  • Dealing with Missing Data
  • Dealing with Outliers
  • Creating Histogram and Scatter Plot
  • Performing Descriptive Statistics
  • Performing Transformations
  • Plotting side-by-side histograms
  • Understanding Skewness + Kurtosis
  • Conducting transformations to reach Normality
  • Plotting Histogram with Normal Distribution
  • Plotting Normal Q-Q Plot
  • Creating indicator Variables
  • Finding Duplicated Records

R Chunks for Data Preparation.

Predictive Modelling

Simple Linear Regression

A supervised Machine Learning Technique

Simple Linear Regression includes

  • Calculating Pearson’s Correlation Coefficient
  • Plotting Scatter Plot
  • Plotting Scatter Plot with Regression Line
  • Identifying High-Leverage Points
  • Identifying Influential Observations
  • Checking Normality of Residuals
  • Checking Other Requirements on Residuals
  • Calculating Predictions
  • Plotting and Calculating Confidence and Prediction Interval
  • Dealing with Categories in Regression
  • Identifying Importance of Predictors
  • Plotting Importance Chart for Regression Predictors

R Chunks for Simple Linear Regression.

Predictive Modelling

Multiple Linear Regression

A supervised Machine Learning Technique

Multiple Linear Regression includes

  • Computing Correlation Matrix
  • Showing Correlation Matrix
  • Running Regression
  • Displaying 3-D Plot
  • Calculating Prediction with Confidence and Prediction Interval
  • Showing High Leverage Points and Influential Observations
  • Making Indicator Variables for Shelf and Running Regression
  • Exploring Multicollinearity
  • Checking Whether Residuals Are Normal
  • Plotting All Residual Plots
  • Plotting All Residual Plots against Xs
  • Testing Model
  • Preparing Data for Pie Chart to Show Relative Importance of Factors
  • Showing Pie Chart of Sum of Squares for Regression Model

R Chunks for Multiple Linear Regression.

Predictive Modelling

Logistic Regression

A supervised Machine Learning Technique

Logistic Regression includes

  • Linear and Logistic Regression for Disease Data
  • Logistic Regression with TelcoChurn Data
  • Logistic Regression with Space Shuttle Data.

The following steps are performed on each dataset:

  • Exploring data
  • Plotting Data as Scatter Plot
  • Plotting Regression Line with 95% CI
  • Calculating McFadden’s Rsquared
  • Calculating Confidence and Prediction Interval for given X data
  • Calculating Odds Ratio
  • Calculating Deviance

R Chunks for Logistic Regression.

Predictive Modelling
Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from - Youtube
Vimeo
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google
Spotify
Consent to display content from - Spotify
Sound Cloud
Consent to display content from - Sound
Save
We use cookies to enhance your experience while using our website. To learn more about the cookies we use and the data we collect, please check our Privacy Settings.
I Accept