Research Article
[Retracted] Analyzing the Performance of Machine Learning Techniques in Disease Prediction
Table 1
Pros and cons from previous studies
| Sl. No. | Authors and methodologies | Pros | Cons |
| 1 | Adaptive neuro-fuzzy inference system. Kavitha and Kannan [16] | Enhancing the accuracy and performance | The cost is high when compared with other methods | 2 | Naive Bayes. Dai et al. [20] | The model applies a specific likelihood of occurrence of the specified task | It is a probability estimation and hence may not be applied for chronic diseases | 3 | K-nearest neighbour. Ross et al. [26] | One of the most commonly used ML algorithms | There are more advanced models that are currently in place | 4 | ANN. Kharche et al. [29] | The interconnection can be effectively rewired, and hence it can adapt to the changing environment | The more hidden layers will impact the overall output and interpretation of the data |
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