Performance Analysis of ANN and Naive Bayes Classification Algorithm for Data Classification

Abstract

Classification is an important data mining technique with a wide range of applications to classify the various types of data existing in almost all areas of our lives. The purpose of this discovery study can be used to estimate the potential of having breast cancer by taking advantage of anthropometric data and collected routine blood analysis parameters. The study was performed using data from patients who were admitted to the clinic with the suspicion of breast cancer. The values of Age (years), BMI (kg/m2), Glucose (mg/dL), Insulin (µU/mL), HOMA, Leptin (ng/mL), Adiponectin (µg/mL), Resistin (ng/mL), MCP-1(pg/dL) were used. In our study, classification algorithms were applied to the data and they were asked to estimate the disease diagnosis. The classification performance of Artificial neural networks and Naïve Bayes classifiers which were applied to data with 9 inputs and one output were calculated and theperformance results were compared. This article sheds light on the performance evaluation based on correct and incorrect data classification examples using ANN and Naïve Bayes classification algorithm. When we look at the performances obtained, it is predicted that using the anthropometric data and the collected routine blood analysis parameters, the potential for diagnosing breast cancer is high using these data.

Fuzzy Expert System for Prediction of Prostate Cancer

“…Saritas et. al [2] has claimed 64.71% true prediction for the same set of data, while online calculator for PC prediction and FPSA/PSA ratio provide only 62.18% and 60.50% respectively. Inclusion of one parameter has definitely increased the number of rules, but the prediction of the designed FES has become more accurate.…”

“…We have applied our proposed FES to analyze the data (given in reference [2]) presented in table VI. Here, the range of different inputs are chosen depending upon the minimum and the maximum values of the respective input variables.…”

“…Rule base Crisp Outputs We have used medical data of the patients as given in reference [2]. Depending on the data set, the range of different inputs are determined.…”

“…Data set containing the information of age, PSA, PV and %FPSA values and biopsy results for 119 patients given in the reference[2]. PCR values are calculated by our FES using Matlab fuzzy logic toolbox.…”

Deteksi Komentar Cyberbullying Pada Media Sosial Berbahasa Inggris Menggunakan Naïve Bayes Classification

“…Naïve Bayes (NB) adalah model pembelajaran statistik berbasis probabilitas dan memiliki asumsi premis bahwa semua atribut sepenuhnya independen pada nilai variabel kelas (Wang, Jiang, & Li, 2015). Teorema Bayes mengasumsikan bahwa semua variabel independen mempertimbangkan nilai variabel kelas (Saritas & Yasar, 2019). Algoritma Naive Bayes Classifier merupakan pengklasifikasian dengan metode probabilitas, yaitu memprediksi peluang di masa depan berdasarkan pengalaman di masa sebelumnya sehingga dikenal sebagai teorema Bayes (Nugroho, 2018).…”