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The following commit(s) were added to refs/heads/trunk by this push:
new eb9979107 [hotfix][website] test removing license to fix build
eb9979107 is described below
commit eb99791077dfddad384e21cacd6e2e80fb25bcb1
Author: Trevor Grant <[email protected]>
AuthorDate: Thu Feb 15 14:08:29 2024 -1000
[hotfix][website] test removing license to fix build
---
.../users/classification/bankmarketing-example.md | 22 ++--------------------
1 file changed, 2 insertions(+), 20 deletions(-)
diff --git
a/website/documentation/users/classification/bankmarketing-example.md
b/website/documentation/users/classification/bankmarketing-example.md
index fa5567300..2037a7a42 100644
--- a/website/documentation/users/classification/bankmarketing-example.md
+++ b/website/documentation/users/classification/bankmarketing-example.md
@@ -1,24 +1,6 @@
-<!--
- Licensed to the Apache Software Foundation (ASF) under one or more
- contributor license agreements. See the NOTICE file distributed with
- this work for additional information regarding copyright ownership.
- The ASF licenses this file to You under the Apache License, Version 2.0
- (the "License"); you may not use this file except in compliance with
- the License. You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
--->
---
layout: default
-title:
-
-
+title: Bank Marketing Example
---
Notice: Licensed to the Apache Software Foundation (ASF) under one
@@ -66,4 +48,4 @@ This example consists of 3 classes:
When you run the main method of BankMarketingClassificationMain it parses the
dataset using the TelephoneCallParser and trains
a logistic regression model with 20 runs and 20 passes. The
TelephoneCallParser uses Mahout's feature vector encoder
-to encode the features in the dataset into a vector. Afterwards the model is
tested and the learning rate and AUC is printed accuracy is printed to standard
output.
\ No newline at end of file
+to encode the features in the dataset into a vector. Afterwards the model is
tested and the learning rate and AUC is printed accuracy is printed to standard
output.
