AWESOME DATA SCIENCE
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is a machine learning algorithm that is used solved calssification problems. It's based on applying Bayes' theorem with strong independence assumptions between the features.
Section: Comparison
Section: On Wikipedia
Section: Interpretable Models · Good classification, poor estimation using conditional probabilities.
Section: Algorithms · is a machine learning algorithm that is used solved calssification problems. It's based on applying Bayes' theorem with strong independence assumptions between the features.
A Python library that facilitates the comparison of two DataFrames in Pandas, Polars, Spark and more. The library goes beyond basic equality checks by providing detailed insights into discrepancies at both row and column levels.
Easily plottable and understandable classification.
The tree provides an interpretation.
is a fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
is an approach to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
scikit-learn clustering algorithms.