# High-Performance Machine Learning Framework with C++ Acceleration

## Documentation for package ‘VectorForgeML’ version 0.1.0

- DESCRIPTION file.

## Help Pages

accuracy_score | Accuracy Score
ColumnTransformer | Column Transformer
ColumnTransformer-class | Column Transformer
confusion_matrix | Confusion Matrix
confusion_stats | Confusion Matrix Statistics
DecisionTree | Decision Tree Model
DecisionTree-class | Decision Tree Model
drop_constant_columns | Drop Constant Columns
f1_score | F1 Score
find_best_k | Find Best K
fit_linear_model | Fit Linear Model (Fast C++ backend)
KMeans | KMeans Clustering
KMeans-class | KMeans Clustering
KNN | K-Nearest Neighbors Model
KNN-class | K-Nearest Neighbors Model
LabelEncoder | Label Encoder
LabelEncoder-class | Label Encoder
LinearRegression | Linear Regression Model
LinearRegression-class | Linear Regression Model
LogisticRegression | Logistic Regression Model
LogisticRegression-class | Logistic Regression Model
macro_f1 | Macro Precision
macro_precision | Macro Precision
macro_recall | Macro Precision
MinMaxScaler | Standard Scaler
MinMaxScaler-class | Standard Scaler
mse | Mean Squared Error
OneHotEncoder | One Hot Encoder
OneHotEncoder-class | One Hot Encoder
PCA | Principal Component Analysis
PCA-class | Principal Component Analysis
Pipeline | Pipeline
Pipeline-class | Pipeline
plot_confusion_matrix | Plot Confusion Matrix
precision_score | Precision Score
predict_linear_model | Predict Linear Model
r2_score | R2 Score
RandomForest | Random Forest Model
RandomForest-class | Random Forest Model
recall_score | Recall Score
RidgeRegression | Ridge Regression Model
RidgeRegression-class | Ridge Regression Model
rmse | Root Mean Squared Error
SoftmaxRegression | Softmax Regression Model
SoftmaxRegression-class | Softmax Regression Model
StandardScaler | Drop Constant Columns
StandardScaler-class | Drop Constant Columns
train_test_split | Train Test Split