A Novel Learning Scheme for Chebyshev Functional Link Neural Networks

<div class="floats-full-page floats-full-page-other"><h2>Table 7</h2><div class="floats-full-page-caption">Weight Matrix of classes to Penalize.</div><div class="floats-full-page-content"><table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr /></td></tr><tr><td align="left"> Real Classification</td><td align="center" colspan="2"> Model Classification</td></tr><tr><td align="left"></td><td align="center"> Class 1</td><td align="center"> Class 2 </td></tr><tr><td align="center" colspan="3"><hr /></td></tr><tr><td align="left"> Class 1</td><td align="center"> 0</td><td align="center"><span style="width: 17.299999px;"><svg height="11.925" id="M226" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 17.299999 11.925" width="17.299999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,7.775)"><path d="M615 290q0 -148 -114 -245q-65 -57 -125 -57q-39 0 -62 27t-29 70q-31 -41 -72 -69t-74 -28q-49 0 -82.5 43t-33.5 124q0 97 55 174.5t148 124.5l15 -24q-59 -45 -94 -113t-35 -146q0 -58 19.5 -88.5t48.5 -30.5q33 0 62 34.5t45 101.5q16 73 20 135l80 17l5 -6&#10;q-11 -37 -23.5 -100t-12.5 -92q0 -47 16.5 -71.5t44.5 -24.5q62 0 95.5 67t33.5 160q0 107 -63 152l1 9q14 14 45 14q29 0 57.5 -44t28.5 -114z" id="x1D714"></path></g>
<g transform="matrix(.012,-0,0,-.012,10.912,11.863)"><path d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z" id="x32"></path></g>
</svg></span></td></tr><tr><td align="left"> Class 2</td><td align="center"><span style="width: 17.299999px;"><svg height="11.925" id="M227" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 17.299999 11.925" width="17.299999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,7.775)"><path d="M615 290q0 -148 -114 -245q-65 -57 -125 -57q-39 0 -62 27t-29 70q-31 -41 -72 -69t-74 -28q-49 0 -82.5 43t-33.5 124q0 97 55 174.5t148 124.5l15 -24q-59 -45 -94 -113t-35 -146q0 -58 19.5 -88.5t48.5 -30.5q33 0 62 34.5t45 101.5q16 73 20 135l80 17l5 -6&#10;q-11 -37 -23.5 -100t-12.5 -92q0 -47 16.5 -71.5t44.5 -24.5q62 0 95.5 67t33.5 160q0 107 -63 152l1 9q14 14 45 14q29 0 57.5 -44t28.5 -114z" id="x1D714"></path></g>
<g transform="matrix(.012,-0,0,-.012,10.912,11.863)"><path d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" id="x31"></path></g>
</svg></span></td><td align="center"> 0</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr" /></td></tr></table></td></tr></table></div></div>

Table 7 | A Novel Learning Scheme for Chebyshev Functional Link Neural Networks

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Table 7: A Novel Learning Scheme for Chebyshev Functional Link Neural Networks

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Table 7

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Advances in Artificial Neural Systems

A Novel Learning Scheme for Chebyshev Functional Link Neural Networks

Table 7