predict.PIE {PIE} | R Documentation |
Make Predictions for PIE
Description
predicts the response of a PIE
object using new data.
Usage
## S3 method for class 'PIE'
predict(object, X, X_orig, ...)
Arguments
object |
A fitted |
X |
A matrix for the dataset with features expanded using numerical splines. |
X_orig |
A matrix for the dataset with original features without numerical splines. |
... |
Not used. Other arguments to |
Details
Make Predictions for PIE
This function predicts the response of a PIE
object.
The PIE_predict function use generate predictions on dataset given the coefficients of group lasso and coefficients for XGBoost Trees
Value
A list containing:
total |
The predicted value of the whole model for given features |
white_box |
The contribution of group lasso for the given features |
black_box |
The contribution of XGBoost model for the given features |
Examples
# Load the training data
data("winequality")
# Which columns are numerical?
num_col <- 1:11
# Which columns are categorical?
cat_col <- 12
# Which column is the response?
y_col <- ncol(winequality)
# Data Processing (the first 200 rows are sampled for demonstration)
dat <- data_process(X = as.matrix(winequality[1:200, -y_col]),
y = winequality[1:200, y_col],
num_col = num_col, cat_col = cat_col, y_col = y_col)
# Fit a PIE model
fold <- 1
fit <- PIE_fit(
X = dat$spl_train_X[[fold]],
y = dat$train_y[[fold]],
lasso_group = dat$lasso_group,
X_orig = dat$orig_train_X[[fold]],
lambda1 = 0.01, lambda2 = 0.01, iter = 5, eta = 0.05, nrounds = 200
)
# Prediction
pred <- predict(fit,
X = dat$spl_validation_X[[fold]],
X_orig = dat$orig_validation_X[[fold]]
)
[Package PIE version 1.0.0 Index]