.

Recently (6/8/2018), I saw a post about a new R package "naniar", which according to the package documentation, "provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data." naniar is authored…

ContinueAdded by Blaine Bateman on July 3, 2018 at 10:30am — No Comments

There are many good and sophisticated feature selection algorithms available in R. Feature selection refers to the machine learning case where we have a set of predictor variables for a given dependent variable, but we don’t know a-priori which predictors are most important and if a model can be improved by eliminating some predictors from a model. In linear regression, many students are taught to fit a data set to find the best model using so-called “least squares”. In most…

ContinueAdded by Blaine Bateman on April 30, 2018 at 7:30am — No Comments

In this article we will review application of clustering to customer order data in three parts. First, we will define the approach to developing the cluster model including derived predictors and dummy variables; second we will extend beyond a typical “churn” model by using the model in a cumulative fashion to predict customer re-ordering in the future defined by a set of time cutoffs; last we will use the cluster model to forecast actual revenue by estimating the ordering parameter…

ContinueAdded by Blaine Bateman on March 27, 2018 at 10:00am — 8 Comments

If you are like me, back in engineering school you learned linear regression as a way to “fit a line to data” and probably called in “least squares”. You probably extended it to multiple variables affecting a single dependent variable. In a statistics class you had to calculate a bunch of stuff and estimate confidence intervals for those lines. And that was probably about it for a long time, unless you were focusing on math or statistics. You may have…

ContinueAdded by Blaine Bateman on March 23, 2018 at 6:30am — 2 Comments

- 5 Data Cleansing Tools
- ScalaCL - Run Scala on GPUs
- 2016 Trends in Big Data & Network Security
- Exploring the VW scandal with graph analysis
- Be A Star Data Scientist: Certifications For Overall Excellence
- Walmart Kaggle: Trip Type Classification
- 24 Uses of Statistical Modeling (Part I)
- What's Trending on Etsy?
- Scraping Lottery Data
- Architecture of Data Science Projects
- A data scientist shares his passions

Posted 24 June 2021

© 2021 TechTarget, Inc. Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions