summary_stats: Summary statistics for the all datasets

In pmlbr: Interface to the Penn Machine Learning Benchmarks Data Repository

Summary statistics for the all datasets

Description

Summary statistics for the all datasets

Usage

summary_stats

Format

A data frame with 10 variables:

dataset:

Dataset name

n_instances:

Number of data observations (equal to number of rows)

n_features:

Total number of features (number of columns - 1)

n_binary_features:

Number of binary features

n_categorical_features:

Number of categorical features

n_continuous_features:

Number of continuous features

n_classes:

Number of classes in target variable

endpoint_type:

Value type of endpoint/target (can be binary, categorical or continuous)

imbalance:

Imbalance metric, where zero means that the dataset is perfectly balanced and the higher the value, the more imbalanced the dataset

task:

Type of problem/task. Can be classification or regression.

Source

https://github.com/EpistasisLab/pmlb

pmlbr documentation built on Sept. 29, 2023, 1:06 a.m.