candisc | Canonical Discriminant Analysis |
census2020 | Japanese Population Census Data 2020 令和2年度国勢調査データ |
centropy | Impurity Measure Functions |
cuttree_dt | Cut a Tree |
cuttree_dt_JPH | 決定木の切断 |
DecTree | Decision Tree |
DecTree_JPH | 決定木の作成 |
Divide | Divide a set of objects into two homogeneous sets |
DivideM | Divide a set of objects into two homogeneous sets with resampling |
entropy | Impurity Measure Functions |
feature_imp_dt | Calculation of Feature Importance |
gini | Impurity Measure Functions |
gini_JPH | 不純度の指標の計算 |
lazy.tree | lazy.tree: Some Decision Tree Functions for lazy boys and girls |
lazy.tree_JPH | lazy.tree: Some Decision Tree Functions for lazy boys and girls |
mis.match | Impurity Measure Functions |
Mode | Mode of the Input Vector |
node_info_dt | Display the Definition of the Node |
node_info_dt_JPH | ノードの定義の表示 |
plot2d_dt | Plot the Border Lines Calculated by the Decision Tree |
plot_dt | Plot Decision Tree |
predict_dt | Calculate the Predicted Values from the Regressor Matrix |
predict_dt_JPH | 個体の分類 |
print_hist_dt | Print Division History |
print_leaf_dt | Print the Leaf Node Information |
quantify_x | Quantification of a Categorical Regressor Variable |
quantify_x_JPH | カテゴリカルな説明変数の数値化 |
rect | Test Data for Decision Tree |
simp_ineq | Simplify the Conjunction of Inequalities |
square | Test Data for Classification Tree without Error |
square2 | Test Data for Classification Tree without Error |
square3 | Test Data for Classification Tree with Error |
square306 | Test Data for Classification Tree without Error |
summary_dt | Calculate Summary Statistics of a Decision Tree |
summary_dt_JPH | 決定木の結果の要約 |
treesim_dt | Similarity Index of Two Trees |
treesim_dt_JPH | 決定木の類似度の指標の計算 |
univar | Test Data for Univariate Regression Tree |
variance | Impurity Measure Functions |