best practice to apply logic regression in azure ml

Question

I am developing my logic regression model and I want to use azure ml to do so. What is the best proactive way to do it? How to start

Answer 1

Hello @kevin

Thanks for reaching out to us, I would suggest you start from below sample for regression project - https://github.com/Azure/MachineLearningDesigner/blob/master/articles/samples/text-classification-wiki.md

This sample demonstrates how to use text analytics modules to build a text classification pipeline in Azure Machine Learning designer.

The goal of text classification is to assign some piece of text to one or more predefined classes or categories. The piece of text could be a document, news article, search query, email, tweet, support tickets, customer feedback, user product review etc. Applications of text classification include categorizing newspaper articles and news wire contents into topics, organizing web pages into hierarchical categories, filtering spam email, sentiment analysis, predicting user intent from search queries, routing support tickets, and analyzing customer feedback.

This pipeline trains a multiclass logistic regression classifier to predict the company category with Wikipedia SP 500 dataset derived from Wikipedia.

This is a good example if you want to design your project, I hope this helps!

Regards,
Yutong

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