Results 31 to 40 of about 131,003 (284)

Fast and accurate sentiment classification using an enhanced Naive Bayes model

, 2013
We have explored different methods of improving the accuracy of a Naive Bayes classifier for sentiment analysis. We observed that a combination of methods like negation handling, word n-grams and feature selection by mutual information results in a ...
Arora, Ishan, Bhatia, Arjun, Narayanan, Vivek   +2 more
core   +1 more source

Bayes and Naive Bayes Classifier

, 2014
The Bayesian Classification represents a supervised learning method as well as a statistical method for classification. Assumes an underlying probabilistic model and it allows us to capture uncertainty about the model in a principled way by determining probabilities of the outcomes.
Vikramkumar, B, Vijaykumar, Trilochan
openaire   +2 more sources

Filtering Useful App Reviews Using Naïve Bayes—Which Naïve Bayes?

AI
App reviews provide crucial feedback for software maintenance and evolution, but manually extracting useful reviews from vast volumes is time-consuming and challenging.
Pouya Ataei, Sri Regula, Daniel Staegemann, Saurabh Malgaonkar   +3 more
doaj   +1 more source

A Decision tree-based attribute weighting filter for naive Bayes [PDF]

, 2006
The naive Bayes classifier continues to be a popular learning algorithm for data mining applications due to its simplicity and linear run-time. Many enhancements to the basic algorithm have been proposed to help mitigate its primary weakness--the ...
Hall, Mark A.
core   +1 more source

Dual targeting of RET and SRC synergizes in RET fusion‐positive cancer cells

Molecular Oncology, EarlyView.
Despite the strong activity of selective RET tyrosine kinase inhibitors (TKIs), resistance of RET fusion‐positive (RET+) lung cancer and thyroid cancer frequently occurs and is mainly driven by RET‐independent bypass mechanisms. Son et al. show that SRC TKIs significantly inhibit PAK and AKT survival signaling and enhance the efficacy of RET TKIs in ...
Juhyeon Son, Lily L. Remsing Rix, Bin Fang, Eric A. Welsh, Nicole V. Bremer, Valentina Foglizzo, Paola Roa, Nickole Sigcha‐Coello, Yi Liao, Eric B. Haura, Alexander Drilon, John M. Koomen, Emiliano Cocco, Uwe Rix   +13 more
wiley   +1 more source

A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features [PDF]

, 2016
The Tree Augmented Naive Bayes classifier is a type of probabilistic graphical model that can represent some feature dependencies. In this work, we propose a Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes (HRE-TAN) algorithm, which ...
Freitas, Alex A., Wan, Cen
core   +2 more sources

Edited Naive Bayes

INTELIGENCIA ARTIFICIAL, 2006
Naive Bayes is a well-known and studied algorithm both in statistics and machine learning. Bayesian learning algorithms represent each concept with a single probabilistic summary. This paper presents a variant of the Naive Bayes method, in which the original training set is augmented in the following fashion: Leave-One-Out procedure is applied over the
J.M. Martinez-Otzeta, B. Sierra, E. Lazkano, M. Ardaiz, E. Jauregui   +4 more
openaire   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Lyrics classification using Naive Bayes

2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2018
Text classification is an important and common task in supervised machine learning. The Naive Bayes Classifier is a popular algorithm that can be used for this purpose. The goal of our research was prediction of song performer using Naive Bayes classification algorithm based solely on lyrics. A dataset that has been created consists of lyrics performed
Bužić, Dalibor, Dobša, Jasminka
openaire   +2 more sources

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +10 more
wiley   +1 more source