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I'm new to ML. I'm taking over a Classification project which involves analyzing data for customers which returned a product and I need to determine the return reason (~10 categories). This data was captured at the counter, and could include words like: LGTM (Looks good to me) NFF (No fault found), etc.

I have a training set of 1000 records and when using Google Prediction API I get a "classificationAccuracy" value of "0.82" and 10 labels.

Questions: 1. Any recommended API to analyze this type of data?. 2. What is a good "classificationAccuracy" value?

Thank you

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http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html

You can use the above tutorial to get acquaintance with text classification. Afterwards it should be easier to formulate nontrivial questions to move even further.

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