[PDF][PDF] Is decision tree obsolete in its original form? A burning debate
Accepted: 21 January 2022 Decision trees are one of the oldest and most used (successful)
machine learning algorithms. Over the years various modifications of decision tree have …
machine learning algorithms. Over the years various modifications of decision tree have …
[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 …
[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 …
Big Data in Academia: A Proposed Framework for Improving Students Performance.
IR Banday, M Zaman, SMK Quadri… - Revue d' …, 2022 - search.ebscohost.com
The way people learn has radically changed as a result of information technology. As an
informal method of learning, fragmented learning has become a popular way to learn new …
informal method of learning, fragmented learning has become a popular way to learn new …
[PDF][PDF] Hard voting meta classifier for disease diagnosis using mean decrease in impurity for tree models
Artificial Intelligence (AI) is rapidly transforming our world. With time it has spread into many
business areas [1-3] and is originating in medical field too with the increase in the …
business areas [1-3] and is originating in medical field too with the increase in the …
[PDF][PDF] How M5 Model Trees (M5-MT) on continuous data are used in rainfall prediction: An experimental evaluation
Accepted: 4 June 2022 When using machine learning to predict a class with a continuous
numeric value, there are several issues. Only a few machine-learning approaches are …
numeric value, there are several issues. Only a few machine-learning approaches are …
Attention Res-UNet: Attention residual UNet with focal tversky loss for skin lesion segmentation
During a dermoscopy examination, accurate and automatic skin lesion detection and
segmentation can assist medical experts in resecting problematic areas and decrease the …
segmentation can assist medical experts in resecting problematic areas and decrease the …
Systematic consequence of different splitting indices on the classification performance of random decision forest
Random Forest algorithm eliminates the confines of a decision tree algorithm by reducing
the over-fitting of datasets. It can handle the missing values in an effective manner and is …
the over-fitting of datasets. It can handle the missing values in an effective manner and is …
Performance stagnation of meteorological data of kashmir
Rainfall prediction is the highest research priority in flood-prone areas across the world. This
work assesses the abilities of the Decision Tree (DT), Distributed Decision Tree (DDT) …
work assesses the abilities of the Decision Tree (DT), Distributed Decision Tree (DDT) …
A super ensembled and traditional models for the prediction of rainfall: An experimental evaluation of DT versus DDT versus RF
The main purpose of the current study is to use three traditional and ensemble machine
learning approaches namely Decision tree (DT), Distributed Decision tree (DDT) and …
learning approaches namely Decision tree (DT), Distributed Decision tree (DDT) and …