Dealing with categorical data is an essential part of data preprocessing in many machine learning tasks. Fortunately, encoding categorical data efficiently helps enhance the performance of machine ...
Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...
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Categorical vs. Continuous Data: What’s the Difference?
Data analysis is a fundamental process in any project. However, data can be lumped into different types, with categorical and ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...
This article proposes a decorated parallel coordinate plot for longitudinal categorical data, featuring a jitter mechanism revealing the diversity of observed longitudinal patterns and allowing the ...
Ecologists rely heavily upon statistics to make inferences concerning ecological phenomena and to make management recommendations. It is therefore important to use statistical tests that are most ...
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