Table 2 The progression of feature weights over 10 iterations, where the initial feature weights were set to a balanced and an imbalanced distribution.

From: A computational intelligence approach for classifying dental caries in X-ray images using integrated fuzzy C-means clustering with feature reduction and a weighted matrix scheme

Iterations

Balanced initial weights [0.25, 0.25, 0.25, 0.25]

Imbalanced initial weights [0.1, 0.7, 0.1, 0.1]

x1

x2

x3

x4

x1

x2

x3

x4

1

0.250000000

0.250000000

0.250000000

0.250000000

0.100000000

0.700000000

0.100000000

0.100000000

2

0.202531646

0.367088608

0.227848101

0.202531646

0.080482897

0.758551308

0.080482897

0.080482897

3

0.163724738

0.465336403

0.207214121

0.163724738

0.064698746

0.805903761

0.064698746

0.064698746

4

0.132118804

0.547647924

0.188114469

0.132118804

0.051960705

0.844117886

0.051960705

0.051960705

5

0.106457909

0.616559195

0.170524986

0.106457909

0.041698565

0.874904305

0.041698565

0.041698565

6

0.08567727

0.674252239

0.154393222

0.08567727

0.033442522

0.899672433

0.033442522

0.033442522

7

0.068884241

0.722583425

0.139648093

0.068884241

0.026807809

0.919576573

0.026807809

0.026807809

8

0.055337144

0.763118434

0.126207278

0.055337144

0.021480798

0.935557605

0.021480798

0.021480798

9

0.044424114

0.797169068

0.113982704

0.044424114

0.017206816

0.948379553

0.017206816

0.017206816

10

0.035643255

0.825828964

0.102884526

0.035643255

0.013779679

0.958660963

0.013779679

0.013779679

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