objective(s): this study addresses feature selection for breast cancer diagnosis. the present process uses a wrapper approach using ga-based on feature selection and ps-classifier. the results of experiment show that the proposed model is comparable to the other models on wisconsin breast cancer datasets. materials and methods: to evaluate effectiveness of proposed feature selection method, we ...

nowadays diabetes disease is one of the main problems of health domain and it’s known as the fourth factor of death in the world. the main problem with this dangerous disease is the late or weak diagnosis. the reason of weak diagnosis is because sometimes doctors aren’t able to select the right patterns or they can’t use the standard patterns very well, so the outcome is that the disease will b...

Imbalanced classification techniques have been applied widely in the field of data mining. It is used to classify imbalanced classes that are not equal number samples. The problem performance tends class with more samples while few will obtain poor performance. This can be occurred Qur’anic due different verses. Many studies classified verses, which depended on traditional classification. Howev...

Automatic Modulation Classification (AMC) is a rapidly evolving technology, which can be employed in software defined radio structures, especially 5G and 6G technology. Machine Learning (ML) provide novel efficient technology for modulation classification, systems working low signal to noise ratio (SNR). In this article, two dynamic not reliant on received phase lock frequency are presented, wi...

     Data reduction is used to aggregate or amalgamate the large data sets into smaller and manageable information pieces in order to fast and accurate classification of different attributes. However, excessive spatial or spectral data reduction may result in losing or masking important radiometric information. Therefore, we conducted this research to evaluate the effectiveness of the different...

induction motor bearing is one of the key parts of the machine and its analysis and interpretation are important for fault detection. in the present work vibration signal has been taken for the classification i.e. bearing is healthy (h) or defective (d). for this purpose, clustering based classification of bearing vibration data has been carried out using principal component analysis (pca) and ...