In the realm of data science and machine learning, ‘Use the Model to Predict’ is not just a phrase, but a powerful concept that can unlock valuable insights.
In this article, we will explore the intricacies of predictive modeling and retraining using Python.
Whether you want to apply an existing model for predictions or delve into retraining with fresh data, this guide will provide you with essential insights and practical steps to ensure success in your data-driven endeavors.
python predicat_apk.py <apkPath>
python lstm.py
It will read data from the new_train.csv.
About the model and training process you can reference.
If you want to retrain with your own data, pay attention to the training set you use. As the doc above showing, choosing a training set can be tricky and can affect accuracy.
The training set in the doc above was randomly selected from our sample, and the accuracy was quite surprising to us.I hope it was helpful
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