29. Why is Naive Bayes called ‘naive’? Naive Bayes is called naive because it makes the general assumption that all the data present are unequivocally important and independent of each other. This is not true and won’t hold up in a real-world scenario. 30. What is the simple differenc...
Naive Bayes is a data science algorithm. It has the word ‘Bayes’ in it because it is based on the Bayes theorem, which deals with the probability of an event occurring given that another event has already occurred. It has ‘naive’ in it because it makes the assumption that each variab...
Apache™ Mahout is a library of scalable machine-learning algorithms, implemented on top of Apache Hadoop® and using the MapReduce paradigm.Machine learningis a discipline of artificial intelligence focused on enabling machines to learn without being explicitly programmed, and it is commonly used ...
“In a previous role, I felt the baseline model we were using - a Naive Bayes recommender - wasn’t providing precise enough search results to users. I felt that we could obtain better results with an elastic search model. I presented my idea and an A/B testing strategy to persuade the...
Instead of simply describing the aggregated results, we employ machine learning algorithms – Naive Bayes, Random Forest and Categorical Boosting – in an attempt to classify users into groups, with a focus on the features that most effectively separate responses. We also demonstrate a way to ...
BERT with Multinomial Naive Bayes Multinomial Naive Bayes (MNB) is a probabilistic classifier commonly used for text classification tasks (Saini & Tripathi,2018), such as tagging. It assumes feature independence and models the likelihood of observing specific word counts in a document using the multi...
Basics of Naive Bayes in NLP Naive Bayes makes use ofBag of Wordstechniques, treating the order of words as irrelevant. It calculates the probability of a document belonging to a specific category based on the probability of words occurring within that category. ...
How would you improve a spam detection algorithm that uses naive Bayes? Have you been working with white lists? Positive rules? (In the context of fraud or spam detection) What is star schema? Lookup tables? Can you perform logistic regression with Excel? (yes) How? (use linest on log...
算法举例:常见的有监督机器学习算法包括支持向量机(Support Vector Machine, SVM),朴素贝叶斯(Naive Bayes),逻辑回归(Logistic Regression),K近邻(K-Nearest Neighborhood, KNN),决策树(Decision Tree),随机森林(Random Forest),AdaBoost以及线性判别分析(Linear Discriminant Analysis, LDA)等...
5. How Can You Choose a Classifier Based on a Training Set Data Size? When the training set is small, a model that has a right bias and low variance seems to work better because they are less likely to overfit. For example, Naive Bayes works best when the training set is large. Mo...