Machine learning methods in drug discovery
The advancements of information technology and related processing techniques have
created a fertile base for progress in many scientific fields and industries. In the fields of drug …
created a fertile base for progress in many scientific fields and industries. In the fields of drug …
Machine learning: a review of classification and combining techniques
Supervised classification is one of the tasks most frequently carried out by so-called
Intelligent Systems. Thus, a large number of techniques have been developed based on …
Intelligent Systems. Thus, a large number of techniques have been developed based on …
[PDF][PDF] Fast binary feature selection with conditional mutual information.
F Fleuret - Journal of Machine learning research, 2004 - jmlr.org
We propose in this paper a very fast feature selection technique based on conditional
mutual information. By picking features which maximize their mutual information with the …
mutual information. By picking features which maximize their mutual information with the …
[HTML][HTML] Naive Bayes classifier–An ensemble procedure for recall and precision enrichment
Data is essential for an organization to develop and make decisions efficiently and
effectively. Machine learning classification algorithms are used to categorize observations …
effectively. Machine learning classification algorithms are used to categorize observations …
Data preparation for data mining
Data preparation is a fundamental stage of data analysis. While a lot of low-quality
information is available in various data sources and on the Web, many organizations or …
information is available in various data sources and on the Web, many organizations or …
Landslide susceptibility assessment in vietnam using support vector machines, decision tree, and Naive Bayes Models
D Tien Bui, B Pradhan, O Lofman… - Mathematical problems …, 2012 - Wiley Online Library
The objective of this study is to investigate and compare the results of three data mining
approaches, the support vector machines (SVM), decision tree (DT), and Naïve Bayes (NB) …
approaches, the support vector machines (SVM), decision tree (DT), and Naïve Bayes (NB) …
A correlation-based feature weighting filter for naive Bayes
Due to its simplicity, efficiency, and efficacy, naive Bayes (NB) has continued to be one of the
top 10 algorithms in the data mining and machine learning community. Of numerous …
top 10 algorithms in the data mining and machine learning community. Of numerous …
Discrete Bayesian network classifiers: A survey
We have had to wait over 30 years since the naive Bayes model was first introduced in 1960
for the so-called Bayesian network classifiers to resurge. Based on Bayesian networks …
for the so-called Bayesian network classifiers to resurge. Based on Bayesian networks …
Ensemble machine learning-based recommendation system for effective prediction of suitable agricultural crop cultivation
Agriculture is the most critical sector for food supply on the earth, and it is also responsible
for supplying raw materials for other industrial productions. Currently, the growth in …
for supplying raw materials for other industrial productions. Currently, the growth in …
A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction
Feature selection is one of the crucial data preprocessing techniques for improving the
performance of machine learning (ML) models. Recently, metaheuristic feature selection …
performance of machine learning (ML) models. Recently, metaheuristic feature selection …