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Fig 1.

Basic steps for the proposed methodology for the leukemia classification.

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Table 1.

Performance evaluation measures.

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Table 1 Expand

Table 2.

Performance measure analysis using Linear Regression.

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Fig 2.

Confusion Matrix using Linear Regression.

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Table 3.

Results analysis using Random Forest.

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Fig 3.

Confusion Matrix using Random Forest.

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Table 4.

Results analysis using SVM.

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Fig 4.

Confusion Matrix using SVM.

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Table 5.

Results analysis using LSTM.

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Fig 5.

Confusion Matrix using LSTM.

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Fig 6.

(a) Model Loss and (b) Accuracy using LSTM Mode.l.

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Table 6.

Comparisons of the Results using Machine Learning and Deep learning models.

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Table 6 Expand

Table 7.

A comparison of the results of the 25 features that were used for this study with other feature sets from earlier leukemia classification studies.

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Table 7 Expand

Fig 7.

Comparisons of the Results using Machine learning on selected 25 Features.

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