Man pages for RomeroBarata/dcme
Data Complexity Measures
| corr_abs | Mean Absolute Correlation Coefficient. |
| F1 | Fisher's Discriminant Ratio (F1). |
| F2 | Volume of Overlap Region (F2). |
| IR | The Imbalance Ratio (IR) of a Data Set. |
| N2 | Ratio of Average Intra/Inter Class NN Distance. |
| N3 | Error Rate of 1-NN Classifier. |
| N4 | Nonlinearity of the 1-NN Classifier. |
| num_classes | The Number of Classes in the Data Set. |
| num_examples | The Number of Observations in the Data Set. |
| num_examples_majority | The Number of Observations in the Majority Class. |
| num_examples_minority | The Number of Observations in the Minority Class. |
| num_features | The Number of Features in the Data Set. |
| num_features_binary | The Number of Binary Features in the Data Set. |
| num_features_categorical | The Number of Categorical Feautures in the Data Set. |
| num_features_numeric | The Number of Numeric Features in the Data Set. |
| proportion_examples_majority | The Proportion of Majority Examples in the Data Set. |
| proportion_examples_minority | The Proportion of Minority Examples in the Data Set. |
| proportion_features_binary | The Proportion of Binary Features in the Data Set. |
| proportion_features_categorical | The Proportion of Categorical Features in the Data Set. |
| proportion_features_numeric | The Proportion of Numeric Features in the Data Set. |
| sd_ratio | The Geometric Mean Ratio of Standard Deviations. |
| split_x_and_y | Split a Data Set into Predictors and Target. |
| T2 | Average Number of Points per Dimension (T2). |
