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SGD training snippet for Medium post
def sgd(x_train, y_train, x_valid, y_valid, variance_threshold=0.1):
threshold = VarianceThreshold(variance_threshold)
sgd_classifier = SGDClassifier(
alpha=1./len(x_train),
class_weight='balanced',
loss='log', penalty='elasticnet',
fit_intercept=False, tol=0.001, n_jobs=-1)
bagging = BaggingClassifier(
base_estimator=sgd_classifier,
bootstrap_features=True,
n_jobs=-1, max_samples=0.5, max_features=0.5)
x_thresh = threshold.fit_transform(x_train)
bagging.fit(x_thresh, y_train)
train_metrics = build_metrics(bagging, x_thresh, y_train)
x_thresh = threshold.transform(x_valid)
valid_metrics = build_metrics(bagging, x_thresh, y_valid)
return bagging, train_metrics, valid_metrics
def build_metrics(model, X, y):
probs = model.predict_proba(X)
preds = np.argmax(probs, axis=1)
metrics = dict(
probs=probs,
preds=preds,
loss=log_loss(y, probs),
accuracy=np.mean(preds == y))
return namedtuple('Predictions', metrics.keys())(**metrics)
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