On the Learnability of Concepts With Applications to Comparing Word Embedding Algorithms
Table 3: Average Performance of a Linear Classifiers using LIWC word lists on GloVe word embeddings to identify members of its own set. Random lists are also tested to obtain a p-value and compare performances. These embeddings perform better than random embeddings, after one thousand iterations and random word lists resulting in a p-value of <0.001
['[BOLD] L', 'Size', 'Accuracy', 'Recall', 'FPR', 'Prec', 'AUC']
Lrandom(avg) shows the average performance of concepts defined from random word lists. Lrandom(max) shows the best performing random word list for each test statistic.