In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about…

Data Intelligence, Business Analytics

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- Discussions (4)

I would like to know What is the importance understanding underlying data distributions in a dataset before applying any machine learning algorithm - it can be either prediction or classification…Continue

Tags: learning, machine, statistics

Started Aug 25, 2014

2 Replies

Need advice Dear Community,I have a situation, where I need to classify items into groups (lets say 6). When I ran k-means 90% of my data fall in 1 group remaining 10% fall in other groups. What's…Continue

Tags: clustering

Started this discussion. Last reply by Edmund Freeman Mar 15, 2014.

Leigh Sneddon commented on suresh kumar Gorakala's blog post Data Science with R

"Are there any free libraries of R code that do things like tree classification, logistic regression, support-vector matching, entropy-based variable selection, classification using linear discriminant functions, cross-validation to control…"

Jan 1, 2016

suresh kumar Gorakala posted a blog post### Data Science with R

As R programming language becoming popular more and more among data science group, industries, researchers, companies embracing R, going forward I will be writing posts on learning Data science using R. The tutorial course will include topics on data types of R, handling data using R, probability theory, Machine Learning, Supervised – unSupervised learning, Data Visualization using R, etc. Before going further, let’s just see some stats and tidbits on data science and R."A …See More

Dec 29, 2015

suresh kumar Gorakala's discussion was featured### Advice on using similarity metrics in content based recosystems

For the below dataset, what would be the best similarity metric in recommending movies to user1? Currently I'm using TFIDF to calculate weights for movie attributes and Cosine similarity to calculate the similarity values.If any attributes occurs more then its weight is coming down. For example: If the attribute ACTOR1 is present in 10…See More

Dec 23, 2015

suresh kumar Gorakala posted a discussion### Advice on using similarity metrics in content based recosystems

For the below dataset, what would be the best similarity metric in recommending movies to user1? Currently I'm using TFIDF to calculate weights for movie attributes and Cosine similarity to calculate the similarity values.If any attributes occurs more then its weight is coming down. For example: If the attribute ACTOR1 is present in 10…See More

Dec 22, 2015

Biswarup Ghosh commented on suresh kumar Gorakala's blog post Time Series Analysis using R-Forecast package

"this post is a blatant copy from Rob J Hyndman's book .Atleast acknowledge the source "

Dec 16, 2015

suresh kumar Gorakala's blog post was featured### Collaborative Filtering Recommender Systems - Item Based approach

In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about implementing user based collaborative filtering approach using R. In this post, I will be explaining about basic implementation of Item…See More

Nov 25, 2015

suresh kumar Gorakala commented on suresh kumar Gorakala's blog post Cross Industry Standard for Data Mining

"Thanks Williams Vorhies, great to meet you on the forum."

Nov 11, 2015

suresh kumar Gorakala's blog post was featured### Cross Industry Standard for Data Mining

Recently I have come across a term, CRISP-DM - a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. CRISP-DM, an acronym for Cross Industry Standard Process for Data Mining, is a data mining process model that includes commonly used approaches that data analytics Organizations use to tackle business problems…See More

Oct 23, 2015

William Vorhies commented on suresh kumar Gorakala's blog post Cross Industry Standard for Data Mining

"I was part of the original working group to develop CRISP-DM. It's simple, perhaps obvious, but therefore has stood the test of time."

Oct 22, 2015

suresh kumar Gorakala posted a blog post### Cross Industry Standard for Data Mining

Recently I have come across a term, CRISP-DM - a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. CRISP-DM, an acronym for Cross Industry Standard Process for Data Mining, is a data mining process model that includes commonly used approaches that data analytics Organizations use to tackle business problems…See More

Oct 22, 2015

suresh kumar Gorakala's blog post was featured### Introduction to Logistic Regression in R

In my previous blog I have explained about linear regression. In today’s post I will explain about logistic regression. Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic value, Diastolic value, RACE, etc.. In this scenario we have to build a model which…See More

Oct 7, 2015

suresh kumar Gorakala's blog post was featured### Rscript as Service API

R is getting popular programming language in the area of Data Science. Integrating Rscript with web UI pages is a challenge which many application developers are facing. In this blog post I will explain how we can expose R script as an API, using rApache and Apache webserver. rApache is a project supporting web application development using the R statistical language and environmentand the Apache web server.Exposing Rscipt as API typically involves 3 steps:Pre-requisitesInstalling…See More

Apr 20, 2015

Khurram commented on suresh kumar Gorakala's blog post Regression Analysis using R explained

"As you mentioned regression helps answers to find association, relationship between variables.As per my understanding association relates to correlation where variables completly not dependent to another variable. This…"

Jan 1, 2015

Prof. Dr. Diego Kuonen commented on suresh kumar Gorakala's blog post Regression Analysis using R explained

"Note that the assumptions on the errors of the multiple linear regression model are not satisfied!For example, huge residuals clearly demand a robust fit (e.g. using MM-estimation as in "lmRob" of R package "robust", or…"

Dec 30, 2014

suresh kumar Gorakala commented on suresh kumar Gorakala's blog post Regression Analysis using R explained

"Thanks Justice Moses for the explanation. Will takecare of such things in future"

Dec 29, 2014

JUSTICE MOSES K. AHETO commented on suresh kumar Gorakala's blog post Regression Analysis using R explained

"Hi Suresh,
Many thanks for throwing more light on some basics of regression models/analysis, well done.
The general regression model formula you presented at the top of the graph is correct.
However, the estimated regression model below the graph is…"

Dec 27, 2014

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As R programming language becoming popular more and more among data science group, industries, researchers, companies embracing R, going forward I will be writing posts on learning Data science using R. The tutorial course will include topics on data types of R, handling data using R, probability theory, Machine Learning, Supervised – unSupervised learning, Data Visualization using R, etc. Before going further, let’s just see some stats and tidbits on data science and…

ContinuePosted on December 29, 2015 at 9:30am — 1 Comment

In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about…

Posted on November 23, 2015 at 7:04pm

Recently I have come across a term, CRISP-DM - a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. **CRISP-DM**, an acronym for **Cross Industry Standard Process for Data Mining**, is a data mining process model that includes commonly used approaches that data…

Posted on October 22, 2015 at 10:59am — 2 Comments

In my previous blog I have explained about linear regression. In today’s post I will explain about logistic regression.

Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic value, Diastolic value, RACE, etc.. In this scenario we have to…

Continue Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic value, Diastolic value, RACE, etc.. In this scenario we have to…

Posted on October 7, 2015 at 9:33pm

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