Matrix Factorization in Microsoft Machine Learning Studio: Understanding the Impact of 'Number of Traits'

The name of this kind of Collaborative Filtering is Matrix Factorization. The disadvantage of increasing the 'Number of traits' is that it may lead to overfitting of the model, which means that the model may perform well on the training data but may not generalize well to new data. Additionally, increasing the number of traits may also increase the computational complexity and training time of the model.