Document classification is a growing interest in the research of text mining. Correctly identifying the documents into particular category is still presenting challenge because of large and vast amount of features in the dataset. In regards to the existing classifying approaches, Naïve Bayes is potentially good at serving as a document classification model due to its simplicity. The aim of this paper is to highlight the performance of employing Naïve Bayes in document classification. Results show that Naïve Bayes is the best classifiers against several common classifiers (such as decision tree, neural network, and support vector machines) in term of accuracy and computational efficiency
This work deals with document classification. It is a supervised learning method (it needs a labeled...
Classification is a supervised learning method: the goal is finding the labels of the unknown object...
The work presents the field of document classification. It describes existing techniques with emphas...
Document classification is a growing interest in the research of text mining. Correctly identifying ...
The number of documents in the form of books, scientific articles, reports etc. is always increasing...
Text classification is used to classify the document of similar types . Text classification can be a...
The Naïve Bayes model is used for text classification and the data is considered by using the Naïve ...
News has become a major need for everyone, with news we can get the information needed. News can be ...
The naïve Bayes classifier is a simple form of Bayesian classifiers which assumes all the features a...
Though naïve Bayes text classifiers are widely used because of its simplicity and effectiveness, the...
This thesis explores if classification of financial documents is possible through machine learning w...
Text categorization (also known as text classification) is the task of automatically assigning docum...
World Wide Web has become a huge collection of documents and the amount of documents available is i...
Search engine is a program that searches a data in a database based on keywords entered by the user....
Automated Text categorization and class prediction is important for text categorization to reduce th...
This work deals with document classification. It is a supervised learning method (it needs a labeled...
Classification is a supervised learning method: the goal is finding the labels of the unknown object...
The work presents the field of document classification. It describes existing techniques with emphas...
Document classification is a growing interest in the research of text mining. Correctly identifying ...
The number of documents in the form of books, scientific articles, reports etc. is always increasing...
Text classification is used to classify the document of similar types . Text classification can be a...
The Naïve Bayes model is used for text classification and the data is considered by using the Naïve ...
News has become a major need for everyone, with news we can get the information needed. News can be ...
The naïve Bayes classifier is a simple form of Bayesian classifiers which assumes all the features a...
Though naïve Bayes text classifiers are widely used because of its simplicity and effectiveness, the...
This thesis explores if classification of financial documents is possible through machine learning w...
Text categorization (also known as text classification) is the task of automatically assigning docum...
World Wide Web has become a huge collection of documents and the amount of documents available is i...
Search engine is a program that searches a data in a database based on keywords entered by the user....
Automated Text categorization and class prediction is important for text categorization to reduce th...
This work deals with document classification. It is a supervised learning method (it needs a labeled...
Classification is a supervised learning method: the goal is finding the labels of the unknown object...
The work presents the field of document classification. It describes existing techniques with emphas...