-
A review and its label whether the review is Positive or Negative
-
In the review.txt the ratio of Positive and Negative words is following:
-
A trainig performance using these raw data is:
-
Looks like I am doing a redundant calculation when I udpate weights in a hidden layer. After I optimized this problem:
-
Still, the performance is not quite enough 😕, Let's look at the distribution of words:
-
It looks like, there are too many vauge menaning words(which are close to the zero, or the middle values), let's trim them out. After the trimming, the performance is:
-
😛 The performance is boosted from 200 to 6000.
-
After the training, let's look at the weights in the hidden layer.
-
Using the weights, we can find the similar meaning words!
- Let's take a loot its T-SNE.
- Okay, then what about the positive and negative words?
