Training Model for Sentiment Analysis with Google Prdection API

Question

I am planning to use Google Prediction API for Sentiment Analysis. How can I generate the Traning model for this? Or where can I have any standard training model available for commercial use? I have already tried with the Sentiment Predictor provided in Prediction Gallery of Google Prediction API, but does not seem to work properly.

Answer 1

From my understanding, the "model" for the Google Prediction API is actually not a model, but a suite of models for regression as well as classification. That being said, it's not clear how the Prediction API decides what kind of regression or classification model is used when you present it with training data. You may want to look at how to train a model on the Google Prediction API if you haven't already done so.

If you're not happy with the results of the Prediction API, it might be an issue with your training data. You may want to think about adding more examples to the training file to see if the model comes up with better results. I don't know how many examples you used, but generally, the more you can add, the better.

However, if you want to look at creating one yourself, NLTK is a Python library that you can use to train your own model. Another Python library you can use is scikit-learn.

Hope this helps.

Answer 2

google prediction API is great BUT to train a model you will need...LOT OF DATA. you can use the sentiment model that is alrady trained..