Introduction Here will discuss about the Xgboost model parameter’s tuning using caret package in R.Let’s begin.Open your R console and follow along. To Get Certified for Best Course on Data Science Developed by Data Scientist ,please follow the below link to avail discount https://www.udemy.com/machine-learning-using-r/?couponCode=GREAT_CODE Importing libraries Importing the library mlbench for sonar dataset and caret […]

## Principal Component Analysis in R

How to Perform PCA in R We will discuss here how to perform principal component analysis in R.Although PCA is required for data sets which have very high dimentionality,we will use the iris data set for simple demonstration.Importing the library MASS for iris dataset.The dimentionality of iris data set is 4 excluding the species variable […]

## Logistic Regression output interpretation in R

Introduction This is for you if you are looking for interpretation of p-value,coefficient estimates,odds ratio,logit score and how to find the final probability from logit score in logistic regression in R. Let’s begin !! For Best Course on Data Science Developed by Data Scientist ,please follow the below link to avail discount https://www.udemy.com/machine-learning-using-r/?couponCode=DATA_MASTER Importing libraries,Reading […]

## Avoid Over fitting & start crossvalidation

Introduction If you want to learn what is K-fold cross-validation and how is it done in R,then please follow along.Open your RStudio and have fun!! Course for Beginners: https://www.udemy.com/machine-learning-using-r/?couponCode=DISFOR123 What is Cross-validation A model is usually given a known data set(training data set) on which training is done and unknown dataset(testing data set) against which […]

## Neural Networks for Data Analytics in R

Introduction Precise Demo on Neural Networks for Machine Learning and Data Analytics in R. Open your RStudio and follow along !! Importing libraries #### importing the library MASS for “Boston” dataset library(MASS) library(neuralnet) ## Loading required package: grid Reading data #### Setting the seed so that we get same results each time #### we run […]

## Random Forest in R

Introduction to Random Forest in R Let’s learn from precise Demo on Random Forest in R for Machine Learning and Data Analytics .Open your RStudio and begin typing in the same things as below.Learn by Practice Importing the libraries We need to import the libraries like randomForest in order to use the random forest algorithm […]

## Deep learning in R

Introduction to Deep learning in R It is precise Demo on Deep learning for Machine Learning using h2o in R. H2O is “The Open Source In-Memory, Prediction Engine for Big Data Science”.The H2O R package provides functions for building GLM, GBM, Kmeans, Naive Bayes, Principal Components Analysis, Principal Components Regression, Random Forests and Deep Learning […]

## Decision Tree for data analytics in R

Precise Demo on Decision Tree for Machine Learning and Data Analytics in R.Open RStudio and begin typing in the same things as below.Learn by Practice!! #### Decision Tree is like taking decision on split for each variable in #### order to predict the output #### Importing the required libraries.MASS is used for importing birthwt #### […]

## How to install R and RStudio

R is popular tool used in Machine Learning,data analytics,business analytics,statistical analysis,bioinformatics. To use R efficiently we need another tool which is called as integrated development environment (IDE). RStudio is an integrated development environment (IDE) for R. For using R,we need following 1.Install R 2.Install R-Studio 3.Install R-Packages Mac Users To Install R Go to www.r-project.org […]

## Neural Networks For Machine Learning in R

Neural networks almost mimics the working of human brain.The neurons are connected by axons in human brain.Same way we have neural units in neural networks. Neural networks consist of multiple layers.And each layer has neural units .One is input layer and one is output layer.In between them we have more layers also called as hidden […]