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The research areas such as Web mining, Opinion mining and Text mining focus on studies namely content mining, statistical analysis, prediction, and classification. Multinomial Na\u00efve Bayes (MNB), the state of art of Bayesian classifier is the fastest and simplest text classifier. The objective of the proposed study is to enhance the classification by substituting the conditional probability of existing MNB with probability based frequency computation. A new combination that consists of Pointwise Mutual Information (PMI) and different normalized Term Frequency (TF) is used for computing the conditional probability. The new combinations provide weight to the words based on the information gain carried by the words related to the document that belongs to a class. The robustness of Similarity based Enhanced Conditional Probability MNB (SECP-MNB) is reflected in classification accuracy measurement.<\/jats:p>","DOI":"10.3233\/jifs-181009","type":"journal-article","created":{"date-parts":[[2019,1,25]],"date-time":"2019-01-25T15:56:48Z","timestamp":1548431808000},"page":"1431-1441","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Multinomial Na\u00efve Bayes using similarity based conditional probability"],"prefix":"10.1177","volume":"36","author":[{"given":"B.","family":"Santhi","sequence":"first","affiliation":[{"name":"School of Computing, SASTRA University, Thirumalaisamudram, Thanjavur, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G.R.","family":"Brindha","sequence":"additional","affiliation":[{"name":"School of Computing, SASTRA University, Thirumalaisamudram, Thanjavur, Tamilnadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,1,25]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"41","article-title":"A comparison of event models for naive bayes text classification","volume":"752","author":"McCallum A.","year":"1998","unstructured":"McCallumA., NigamK., A comparison of event models for naive bayes text classification, In: AAAI-98 Workshop on Learning for Text Categorization 752 (1998), 41\u201348.","journal-title":"In: AAAI-98 Workshop on Learning for Text Categorization"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.12.013"},{"key":"e_1_3_2_4_2","first-page":"41","article-title":"A Comparison of Event Models for Naive Bayes Text Classification, in","author":"McCallum A.","year":"1998","unstructured":"McCallumA., NigamK., A Comparison of Event Models for Naive Bayes Text Classification, in, Proc of AAAI-98 Workshop on Learning for Text Categorization, 1998, pp. 41\u201349.","journal-title":"Proc of AAAI-98 Workshop on Learning for Text Categorization"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1561\/1500000011"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.3115\/1118693.1118704"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2012.08.002"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511809071"},{"key":"e_1_3_2_9_2","first-page":"349","article-title":"Automatic Sentiment Analysis in On-line Text","author":"Boiy E.","year":"2007","unstructured":"BoiyE., HensP., DeschachtK., MoensM.F., Automatic Sentiment Analysis in On-line Text, In: ELPUB, 2007, pp. 349\u2013360.","journal-title":"ELPUB"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-45219-5_7"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.02.173"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.11.016"},{"key":"e_1_3_2_13_2","unstructured":"SalvettiF. 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