Heart disease prediction using machine learning techniques: a quantitative review
Heart diseases or the cardiovascular diseases are the main reasons for a large number of
deaths in the world today. Heart disease affects the functioning of blood vessels and can …
deaths in the world today. Heart disease affects the functioning of blood vessels and can …
Knowledge discovery in geographical sciences—A systematic survey of various machine learning algorithms for rainfall prediction
One of the biggest challenges faced by humanity over time is weather prediction. Rainfall
prediction plays a critical role in agricultural sciences, besides it is pivotal in the prediction of …
prediction plays a critical role in agricultural sciences, besides it is pivotal in the prediction of …
[PDF][PDF] Numerical and experimental investigation of meteorological data using adaptive linear M5 model tree for the prediction of rainfall
Real-time predictions are always important for accurate and systematic thinking in planning
future processes. The failure in the availability of current machine learning approaches is a …
future processes. The failure in the availability of current machine learning approaches is a …
A survey of medical image analysis using deep learning approaches
With the expanding development of Deep Learning techniques Medical Image Analysis
have become an active field of research. Medical Image Analysis typically refers to the …
have become an active field of research. Medical Image Analysis typically refers to the …
A pragmatic comparison of supervised machine learning classifiers for disease diagnosis
This study focuses on comparing the different supervised machine learning classifiers such
as Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbour …
as Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbour …
[PDF][PDF] An application of logistic model tree (LMT) algorithm to ameliorate Prediction accuracy of meteorological data
Traditional and ensemble methods are linear models which are considered the most
popular techniques for various learning tasks for the prediction of both nominal and …
popular techniques for various learning tasks for the prediction of both nominal and …
To ameliorate classification accuracy using ensemble distributed decision tree (DDT) vote approach: An empirical discourse of geographical data mining
Weather data of Kashmir province has 6 attributes recorded at three different substations.
This paper proposes a distributed decision tree algorithm and its implementation on …
This paper proposes a distributed decision tree algorithm and its implementation on …
[PDF][PDF] An adaptive gradient boosting model for the prediction of rainfall using ID3 as a base estimator
Accepted: 4 April 2022 While analyzing the data, it is crucial to choose the model that best
matches the circumstance. Many experts in the field of classification and regression have …
matches the circumstance. Many experts in the field of classification and regression have …
Machine learning: An introduction to reinforcement learning
SA Fayaz, S Jahangeer Sidiq… - Machine Learning and …, 2022 - Wiley Online Library
Reinforcement Learning (RL) is a prevalent prototype for finite sequential decision making
under improbability. A distinctive RL algorithm functions with only restricted knowledge of …
under improbability. A distinctive RL algorithm functions with only restricted knowledge of …
Performance evaluation of GINI index and information gain criteria on geographical data: An empirical study based on JAVA and Python
In this paper, generation and performance comparison is established between information
gain and GINI index on raw geographical dataset. Concrete results are drawn, and …
gain and GINI index on raw geographical dataset. Concrete results are drawn, and …