Disease prediction and knowledge extraction in banana crop cultivation using decision tree classifiers

2022 ◽  
Vol 20 (1) ◽  
pp. 107
Author(s):  
A. Anitha
Keyword(s):  
Decision Tree ◽  
Knowledge Extraction ◽  
Disease Prediction ◽  
Crop Cultivation ◽  
Banana Crop

scholarly journals Diabetes disease prediction using decision tree for feature selection

2021 ◽  
Vol 1964 (6) ◽  
pp. 062116
Author(s):  
Jayakumar Sadhasivam ◽  
V Muthukumaran ◽  
J Thimmia Raja ◽  
Rose Bindu Joseph ◽  
Meram Munirathanam ◽  
...  
Keyword(s):  
Feature Selection ◽  
Decision Tree ◽  
Disease Prediction

Heart Disease Prediction System based on Decision Tree Classifier

2019 ◽  
Vol 11 (10-SPECIAL ISSUE) ◽  
pp. 1232-1237
Author(s):  
B. Bavani ◽  
S. Nirmala Sugirtha Rajini ◽  
M.S. Josephine ◽  
V. Prasannakumari
Keyword(s):  
Heart Disease ◽  
Decision Tree ◽  
Disease Prediction ◽  
Prediction System ◽  
Decision Tree Classifier ◽  
Tree Classifier

scholarly journals Heart Disease Prediction

2018 ◽  
Vol 7 (3.12) ◽  
pp. 750
Author(s):  
S Vinothini ◽  
Ishaan Singh ◽  
Sujaya Pradhan ◽  
Vipul Sharma
Keyword(s):  
Heart Disease ◽  
Decision Tree ◽  
Clustering Algorithm ◽  
Learning Algorithm ◽  
Disease Prediction ◽  
Machine Learning Algorithm ◽  
Data Set ◽  
Logistics Regression ◽  
Learning Technique ◽  
Work Integration

Machine learning algorithm are used to produce new pattern from compound data set. To cluster the patient heart condition to check whether his /her heart normal or stressed or highly stressed k-means clustering algorithm is applied on the patient dataset. From  the results of clustering ,it is hard to elucidate and to obtain the required conclusion from these clusters. Hence another algorithm, the decision tree, is used for the exposition of the clusters of . In this work, integration of decision tree with the help of k-means algorithm is aimed. Another learning technique such as SVM and Logistics regression is used. Heart disease prediction results from SVM and Logistics regression were compared. 

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