sap-rpt-1-oss How to use SAP/sap-rpt-1-oss with sap-rpt-1-oss:
pip install git+https://github.com/SAP-samples/sap-rpt-1-oss
# Run a classification task
from sklearn.datasets import load_breast_cancer
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
from sap_rpt_oss import SAP_RPT_OSS_Classifier
# Load sample data
X, y = load_breast_cancer(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
# Initialize a classifier, 8k context and 8-fold bagging gives best performance, reduce if running out of memory
clf = SAP_RPT_OSS_Classifier(max_context_size=8192, bagging=8)
clf.fit(X_train, y_train)
# Predict probabilities
prediction_probabilities = clf.predict_proba(X_test)
# Predict labels
predictions = clf.predict(X_test)
print("Accuracy", accuracy_score(y_test, predictions)) # Run a regression task
from sklearn.datasets import fetch_openml
from sklearn.metrics import r2_score
from sklearn.model_selection import train_test_split
from sap_rpt_oss import SAP_RPT_OSS_Regressor
# Load sample data
df = fetch_openml(data_id=531, as_frame=True)
X = df.data
y = df.target.astype(float)
# Train-test split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
# Initialize the regressor, 8k context and 8-fold bagging gives best performance, reduce if running out of memory
regressor = SAP_RPT_OSS_Regressor(max_context_size=8192, bagging=8)
regressor.fit(X_train, y_train)
# Predict on the test set
predictions = regressor.predict(X_test)
r2 = r2_score(y_test, predictions)
print("R² Score:", r2) 
