Two solutions are proposed and compared, one based on the Naive Bayes classifier and the other on a Linear classifier implemented using TensorFlow. The former obtains an accuracy of over 95% for 23% of the questions while the latter obtains the same accuracy for 60% of the questions. The ...
It classifies an unlabeled observation based on its K (can be any number) surrounding neighbors 17. What Is ‘naive’ in the Naive Bayes Classifier? The classifier is called ‘naive’ because it makes assumptions that may or may not turn out to be correct. The algorithm assumes that the ...
11. Explain how theNaive Bayes classifieris used in NLP. Naive Bayes classifieris a popular choice for text classification tasks inNatural Language Processing(NLP). It's preferred for its simplicity, speed, and effectiveness. Basics of Naive Bayes in NLP Naive Bayes makes use ofBag of Wordstec...
# Create a Naive Bayes classifier. nbc = NaiveBayes() # Load all the training/test ham/spam data. train_hams, train_spams, test_hams, test_spams = nbc.load_data() # Fit the model to the training data. nbc.fit(train_hams, train_spams)...
Large margin classifier: using SVM we not only have a decision boundary, but want the boundary to be as far from the closest training point as possible The closest training examples are called support vectors, since they are the points based on which the decision boundary is drawn SVMs are ...
Give an example of a scenario where you would use Naive Bayes over another classifier? How would you explain what MapReduce does as concise as possible? What is the ROC curve and the meaning of sensitivity, specificity, confusion matrix?
One major drawback of Naive Bayes is that it holds a strong assumption in that the features are assumed to be uncorrelated with one another, which typically is never the case.One way to improve such an algorithm that uses Naive Bayes is by decorrelating the features so that the assumption ...
5 What error metric would you use to evaluate how good a binary classifier is? What if the classes are imbalanced? What if there are more than 2 groups? PRO TIP If asked to predict a response 6 What are various ways to predict a binary response vari- variable during your interview, ...
Constructing a ROC curve to measure and visualize the performace of a binary classifier Posted on December 14, 2012 A very short blog post this time. I wrote a paper on how ROC curves are constructed to measure and visualize the performance of binary classifiers. If you are interested, you...
•Givenafreshnewquestion,wefindthemostsimilar(content-wise),yetnotnecessarilyidentical,pastquestion•Then,inasecondstage,weapplyaclassifierthatestimatesintentsimilarityanddecideswhetherornottoservetheanswerofthispastquestionasanewanswer •4Tomeasuretheeffectivenessofoursystem,weuseacommonofflineevaluationmethod,...