tag:crantastic.org,2005:/authors/7552Latest activity for Krzysztof Byrski2018-01-04T17:40:12Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/699802018-01-04T17:40:12Z2018-01-04T17:40:12ZafCEC was upgraded to version 1.0.2<a href="/packages/afCEC">afCEC</a> was <span class="action">upgraded</span> to version <a href="/packages/afCEC/versions/66861">1.0.2</a><br /><h3>Package description:</h3><p>Active function cross-entropy clustering partitions the n-dimensional data into the clusters by finding the parameters of the mixed generalized multivariate normal distribution, that optimally approximates the scattering of the data in the n-dimensional space, whose density function is of the form: p_1*N(mi_1,^sigma_1,sigma_1,f_1)+...+p_k*N(mi_k,^sigma_k,sigma_k,f_k). The above-mentioned generalization is performed by introducing so called "f-adapted Gaussian densities" (i.e. the ordinary Gaussian densities adapted by the "active function"). Additionally, the active function cross-entropy clustering performs the automatic reduction of the unnecessary clusters. For more information please refer to P. Spurek, J. Tabor, K.Byrski, "Active function Cross-Entropy Clustering" (2017) <doi:10.1016/j.eswa.2016.12.011>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/699462018-01-04T12:40:15Z2018-01-04T12:40:15ZafCEC was upgraded to version 1.0.1<a href="/packages/afCEC">afCEC</a> was <span class="action">upgraded</span> to version <a href="/packages/afCEC/versions/66828">1.0.1</a><br /><h3>Package description:</h3><p>Active function cross-entropy clustering partitions the n-dimensional data into the clusters by finding the parameters of the mixed generalized multivariate normal distribution, that optimally approximates the scattering of the data in the n-dimensional space, whose density function is of the form: p_1*N(mi_1,^sigma_1,sigma_1,f_1)+...+p_k*N(mi_k,^sigma_k,sigma_k,f_k). The above-mentioned generalization is performed by introducing so called "f-adapted Gaussian densities" (i.e. the ordinary Gaussian densities adapted by the "active function"). Additionally, the active function cross-entropy clustering performs the automatic reduction of the unnecessary clusters. For more information please refer to P. Spurek, J. Tabor, K.Byrski, "Active function Cross-Entropy Clustering" (2017) <doi:10.1016/j.eswa.2016.12.011>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/695612017-12-15T18:00:15Z2017-12-15T18:00:15ZafCEC was released<a href="/packages/afCEC">afCEC</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Active function cross-entropy clustering partitions the n-dimensional data into the clusters by finding the parameters of the mixed generalized multivariate normal distribution, that optimally approximates the scattering of the data in the n-dimensional space, whose density function is of the form: p_1*N(mi_1,^sigma_1,sigma_1,f_1)+...+p_k*N(mi_k,^sigma_k,sigma_k,f_k). The above-mentioned generalization is performed by introducing so called "f-adapted Gaussian densities" (i.e. the ordinary Gaussian densities adapted by the "active function"). Additionally, the active function cross-entropy clustering performs the automatic reduction of the unnecessary clusters. For more information please refer to P. Spurek, J. Tabor, K.Byrski, "Active function Cross-Entropy Clustering" (2017) <doi:10.1016/j.eswa.2016.12.011>.</p>crantastic.org