The accuracy of the above-mentioned models was determined and compared. Among the models used, KNN Algorithm had the best accuracy. Significant factors that affect stress were found using KNN, Decision Tree, and Naive Bayes algorithms. With these findings, organizations ca...
CountVectorizersupports counts of N-grams of words or consecutive characters. Once fitted, the vectorizer has built a dictionary of feature indices: >>> count_vect.vocabulary_.get(u'algorithm') The index value of a word in the vocabulary is linked to its frequency in the whole training corpus...
For instance, let's assume we have an algorithm that watches emails a user marks as spam and based on that observation it learns to filter out unwanted spam messages. The experience E in the above situation would be to Watch and recognize what type of mail is marked as spam. Task T wou...
Algorithm 1. Extraction of Feature 1: Input: dataset that has been normalized; 2: Output: A collection of features that have been extracted EsEs; 3: Step 1: for e = 1 to EID//EID—The number of working professionals who have their ID; 4: Calculate how long it will take them to co...
Multinomial Naive Bayes is the classic algorithm for text classification and NLP. For an instance, let’s assume a set of sentences are given which are belonging to a particular class. With new input sentence, each word is counted for its occurrence and is accounted for its commonality and ea...