Leukemia Diagnosis using Machine Learning Classifiers Based on Correlation Attribute Eval Feature Selection

References (28)

1. 1 Classification Based on Decision Tree Algorithm for Machine Learning [DOI]
2. 2 A novel feature-selection approach based on the cuttlefish optimization algorithm for intrusion detection systems [DOI]
3. 3 Acute Lymphoblastic Leukemia Detection and Classification of Its Subtypes Using Pretrained Deep Convolutional Neural Networks [DOI]
4. 4 Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States [DOI]
5. 5 IoMT-Based Automated Detection and Classification of Leukemia Using Deep Learning [DOI]
6. 6 Improved Threshold Based and Trainable Fully Automated Segmentation for Breast Cancer Boundary and Pectoral Muscle in Mammogram Images [DOI]
7. 7 Leukemia Blood Cell Image Classification Using Convolutional Neural Network [DOI]
8. 8 Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer [DOI]
9. 9 Gene Selection and Classification of Microarray Data Using Convolutional Neural Network [DOI]
10. 10 An enhanced J48 classification algorithm for the anomaly intrusion detection systems [DOI]
11. 11 Detection and Classification of Immature Leukocytes for Diagnosis of Acute Myeloid Leukemia Using Random Forest Algorithm [DOI]
12. 12 Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques [DOI]
13. 13 Acute leukemia classification by using SVM and K-Means clustering [DOI]
14. 14 Medical Images Segmentation Based on Unsupervised Algorithms: A Review [DOI]
15. 15 Identification of Full and Partial Class Relevant Genes [DOI]
16. 16 Convergent learning–based model for leukemia classification from gene expression [DOI]
17. 17 Detection and Classification of Acute Lymphocytic Leukemia [DOI]
18. 18 An Analytical Appraisal for Supervised Classifiers’ Performance on Facial Expression Recognition Based on Relief-F Feature Selection [DOI]
19. 19 GFNB: Gini index–based Fuzzy Naive Bayes and blast cell segmentation for leukemia detection using multi-cell blood smear images [DOI]
20. 20 Machine Learning based System for Automatic Detection of Leukemia Cancer Cell [DOI]
21. 21 Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia [DOI]
22. 22 Data Mining Implementation to Predict Sales Using Time Series Method [DOI]
23. 23 Data Mining Attribute Selection Approach for Drought Modelling : A Case Study for Greater Horn of Africa [DOI]
24. 24 Gene clustering with partition around mediods algorithm based on weighted and normalized mahalanobis distance [DOI]
25. 25 A Comparative Analysis and Predicting for Breast Cancer Detection Based on Data Mining Models [DOI]
26. 26 Detection of acute lymphocyte leukemia using k-nearest neighbor algorithm based on shape and histogram features [DOI]
27. 27 custom: A Review of most Recent Lung Cancer Detection Techniques using Machine Learning
28. 28 Data mining using filtering approaches and ensemble methods [DOI]

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