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Stephanie Glen
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  • Jacksonville, FL
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Steve Magnino liked Stephanie Glen's blog post The Lifecycle of Data
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Stephanie Glen's blog post was featured

Comparing Classifiers: Decision Trees, K-NN & Naive Bayes

A myriad of options exist for classification. In general, there isn't a single "best" option for every situation. That said, three popular classification methods— Decision Trees, k-NN & Naive Bayes—can be tweaked for practically every situation.OverviewNaive Bayes and K-NN, are both examples of supervised learning (where the data comes already labeled). …See More
Wednesday
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Stephanie Glen's blog post was featured

The Lifecycle of Data

The lifecycle of data travels through six phases:The lifecycle "wheel" isn't set in stone. While it's common to move through the phases in order, it's possible to move in either direction (i.e. forward, backward) at any stage in the cycle. Work can also happen in several phases at the same time, or you can skip over entire phases. In addition, if new information is…See More
Jun 18
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Stephanie Glen's 2 blog posts were featured
Jun 15
Stephanie Glen's blog post was featured

Alternatives to R-squared (with pluses and minuses)

R-squared can help you answer the question "How does my model perform, compared to a naive model?". However, r2 is far from a perfect tool. Probably the main issue is that every data set contains a certain amount of unexplainable data. R-squared can't tell the difference between the explainable and the unexplainable , so it will go…See More
Jun 10
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Mukesh Bhandarkar liked Stephanie Glen's profile
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Tim Matteson liked Stephanie Glen's blog post The Lifecycle of Data
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Stephanie Glen's 2 blog posts were featured
May 31
Viridiana Veytia liked Stephanie Glen's blog post Bayes Theorem in One Picture
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Rakesh Chintha liked Stephanie Glen's blog post Naive Bayes in One Picture
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Rakesh Chintha liked Stephanie Glen's blog post Cross Validation in One Picture
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Norberto J. Sanchez liked Stephanie Glen's blog post ROC Curve Explained in One Picture
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Stephanie Glen's blog post was featured

Cross Validation in One Picture

Cross Validation explained in one simple picture. The method shown here is k-fold cross validation, where data is split into k folds (in this example, 5 folds). Blue balls represent training data; 1/k (i.e. 1/5) balls are held back for model testing.Monte Carlo cross validation works the same way, except that the balls would be chosen with replacement. In other words, it would be possible for a ball to appear in more than one sample.…See More
May 25
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Nicola Atzori liked Stephanie Glen's blog post Confidence Intervals in One Picture
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Stephanie Glen's 2 blog posts were featured
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Profile Information

Short Bio
Stephanie Glen is Editorial director at DataScienceCentral.com. She is a mathematician and statistician. After working for several years teaching mathematics and statistics at the university level, she created and developed the website StatisticsHowTo.com.
Field of Expertise
Other
Professional Status
Executive
Years of Experience:
14
Your Company:
Andale Publishing, LLC
Industry:
Mathematics Education
Your Job Title:
CEO
Interests:
Contributing

Stephanie Glen's Blog

Comparing Classifiers: Decision Trees, K-NN & Naive Bayes

Posted on June 19, 2019 at 6:49am 0 Comments

A myriad of options exist for classification. In general, there isn't a single "best" option for every situation. That said, three popular classification methods— Decision Trees, k-NN & Naive Bayes—can be tweaked for practically every situation.

Overview

Naive Bayes and K-NN, are both examples of supervised learning (where the…

Continue

Assumptions of Linear Regression in One Picture

Posted on June 15, 2019 at 7:53am 0 Comments

If any of the main assumptions of linear regression are violated, any results or forecasts that you glean from your data will be extremely biased, inefficient or misleading. Navigating all of the different assumptions and recommendations to identify the assumption can be overwhelming (for example, normality has more than half a dozen options for testing).
This image highlights the assumptions and the most common testing options.…
Continue

Alternatives to R-squared (with pluses and minuses)

Posted on June 10, 2019 at 5:30am 0 Comments

R-squared can help you answer the question "How does my model perform, compared to a naive model?". However, r2 is far from a perfect tool. Probably the main issue is that every data set contains a certain amount of unexplainable data. R-squared can't tell the difference between the explainable and the…

Continue

R-Squared in One Picture

Posted on May 31, 2019 at 8:00am 0 Comments

R-squared measures how well your data fits a regression line. More specifically, it's how much variation in the…

Continue

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