Skip to content

switched val to test #1297

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

switched val to test #1297

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 7 additions & 7 deletions website/docs/Use-Cases/Task-Oriented-AutoML.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -74,8 +74,8 @@ The optimization metric is specified via the `metric` argument. It can be either

```python
def custom_metric(
X_val,
y_val,
X_test,
y_test,
estimator,
labels,
X_train,
Expand All @@ -93,8 +93,8 @@ For example,

```python
def custom_metric(
X_val,
y_val,
X_test,
y_test,
estimator,
labels,
X_train,
Expand All @@ -107,9 +107,9 @@ def custom_metric(
import time

start = time.time()
y_pred = estimator.predict_proba(X_val)
pred_time = (time.time() - start) / len(X_val)
val_loss = log_loss(y_val, y_pred, labels=labels, sample_weight=weight_val)
y_pred = estimator.predict_proba(X_test)
pred_time = (time.time() - start) / len(X_test)
val_loss = log_loss(y_test, y_pred, labels=labels, sample_weight=weight_val)
y_pred = estimator.predict_proba(X_train)
train_loss = log_loss(y_train, y_pred, labels=labels, sample_weight=weight_train)
alpha = 0.5
Expand Down