[et_pb_section fb_built=”1″ admin_label=”Course Hero” _builder_version=”4.7.2″ use_background_color_gradient=”on” background_color_gradient_start=”#a5b1ca” background_color_gradient_end=”#09164c” background_image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-background-texture.jpg” background_blend=”overlay” custom_padding=”100px|0px|63px|0px|false|false” animation_style=”slide” animation_direction=”top” animation_intensity_slide=”2%” locked=”off”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”3.25″ custom_margin=”|||” custom_width_px=”1280px”][et_pb_column type=”1_2″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.7.2″ header_font=”|on|||” header_font_size=”42px” header_line_height=”1.3em” background_layout=”dark” custom_padding=”|||” animation_style=”slide” header_font_size_tablet=”” header_font_size_phone=”” header_font_size_last_edited=”on|desktop” locked=”off”]<\/p>\n
[\/et_pb_text][et_pb_text _builder_version=”3.27.4″ text_text_color=”#d4ccff” text_font_size=”16px” text_line_height=”1.9em” locked=”off”]<\/p>\n
Contributed papers from scholars and practitioners are invited on any of the topics below as well as on related issues<\/p>\n
[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_image align_tablet=”center” align_phone=”” align_last_edited=”on|desktop” _builder_version=”4.7.2″ animation_style=”zoom” animation_direction=”left” animation_intensity_zoom=”20%”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”3.22″ custom_padding=”0px||0||false|false”][et_pb_row _builder_version=”3.25″][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb title=”Classification Theory” url=”#” image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-icon_4.jpg” icon_placement=”left” image_max_width=”64px” content_max_width=”1100px” admin_label=”Chapter” _builder_version=”4.7.2″ header_font=”|on|||” header_text_color=”#2e2545″ header_line_height=”1.5em” body_text_color=”#8585bd” body_font_size=”16px” body_line_height=”1.9em” background_color=”#ffffff” custom_margin=”|||” custom_padding=”30px|40px|30px|40px” animation_style=”zoom” animation_direction=”bottom” animation_intensity_zoom=”20%” animation_starting_opacity=”100%” border_color_all_image=”#e02b20″ box_shadow_style=”preset2″ box_shadow_horizontal=”0px” box_shadow_vertical=”0px” box_shadow_blur=”60px” box_shadow_color=”rgba(71,74,182,0.12)” locked=”off”]<\/p>\n
T1. Fuzzy Methods \u2013 T2. Hierarchical Classification \u2013 T3. Non Hierarchical Classification \u2013 T4. Pattern Recognition \u2013 T5.Bayesian Classification \u2013 T6. Classification of Multiway and Functional Data \u2013 T7. Probabilistic Methods for Clustering \u2013 T8. Consensus of Classifications \u2013 T9. Spatial Clustering \u2013 T10. Validity of Clustering \u2013 T11. Neural Networks and Machine Learning Methods for Classification \u2013 T12. Genetic Algorithms \u2013 T13. Classification with Constraints \u2013 T14. Mixture and Latent Class Models for Clustering<\/p>\n
[\/et_pb_blurb][et_pb_blurb title=”Applied Classification and Data Analysis” url=”#” image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-icon_12.jpg” icon_placement=”left” image_max_width=”64px” content_max_width=”1100px” admin_label=”Chapter” _builder_version=”3.0.82″ header_font=”|on|||” header_text_color=”#2e2545″ header_line_height=”1.5em” body_text_color=”#8585bd” body_font_size=”16px” body_line_height=”1.9em” background_color=”#ffffff” custom_margin=”|||” custom_padding=”30px|40px|30px|40px” animation_style=”zoom” animation_direction=”bottom” animation_intensity_zoom=”20%” animation_starting_opacity=”100%” box_shadow_style=”preset2″ box_shadow_horizontal=”0px” box_shadow_vertical=”0px” box_shadow_blur=”60px” box_shadow_color=”rgba(71,74,182,0.12)” locked=”off”]<\/p>\n
A1. Classification of Textual Data \u2013 A2. Data Analysis in Economics and Finance A3. Data Analysis in Environmental Sciences \u2013 A4 Classification in Medical Science \u2013 A5. Cognitive Sciences and Classification A6. Classification in Biology and Ecology \u2013 A7. Data Analysis in Demography \u2013 A8. Classification of Microarray Data \u2013 A9. Data Analysis for Customer Satisfaction and Service Quality Evaluation \u2013 A10. Applications of Data and Web Mining<\/p>\n
[\/et_pb_blurb][et_pb_blurb title=”Data Analysis and Data Science” url=”#” image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-iconArtboard-19-copy-9.jpg” icon_placement=”left” image_max_width=”64px” content_max_width=”1100px” admin_label=”Chapter” _builder_version=”3.0.82″ header_font=”|on|||” header_text_color=”#2e2545″ header_line_height=”1.5em” body_text_color=”#8585bd” body_font_size=”16px” body_line_height=”1.9em” background_color=”#ffffff” custom_margin=”|||” custom_padding=”30px|40px|30px|40px” animation_style=”zoom” animation_direction=”bottom” animation_intensity_zoom=”20%” animation_starting_opacity=”100%” box_shadow_style=”preset2″ box_shadow_horizontal=”0px” box_shadow_vertical=”0px” box_shadow_blur=”60px” box_shadow_color=”rgba(71,74,182,0.12)” locked=”off”]<\/p>\n
D1. Categorical Data Analysis \u2013 D2. Correspondence Analysis \u2013 D3. Biplots \u2013 D4. Factor Analysis and Dimension Reduction Methods \u2013 D5. Discrimination and Classification \u2013 D6. Multiway Methods \u2013 D7. Symbolic Data Analysis \u2013 D8. Non Linear Data Analysis \u2013 D9. Mixture Models \u2013 D10. Multilevel Analysis \u2013 D11. Covariance Structure Analysis D12. Partial Least Squares \u2013 D13. Regression and Classification Trees \u2013 D14. Robust Methods and Data Diagnostics \u2013 D15. Spatial Data Analysis \u2013 D16. Item Response Theory \u2013 D17. Nonparametric and Semiparametric Regression \u2013 D18. Functional Data Analysis D19. Data Mining \u2013 D20. High-dimensional data \u2013 D21. Deep Learning \u2013 D22. Machine Learning \u2013 D23. Statistical Learning \u2013 D24. Network Analysis\u00a0\u2013 D25. Artificial Intelligence<\/p>\n
[\/et_pb_blurb][et_pb_blurb title=”Proximity Structure Analysis” url=”#” image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-icon_16.jpg” icon_placement=”left” image_max_width=”64px” content_max_width=”1100px” admin_label=”Chapter” _builder_version=”3.0.82″ header_font=”|on|||” header_text_color=”#2e2545″ header_line_height=”1.5em” body_text_color=”#8585bd” body_font_size=”16px” body_line_height=”1.9em” background_color=”#ffffff” custom_margin=”|||” custom_padding=”30px|40px|30px|40px” animation_style=”zoom” animation_direction=”bottom” animation_intensity_zoom=”20%” animation_starting_opacity=”100%” box_shadow_style=”preset2″ box_shadow_horizontal=”0px” box_shadow_vertical=”0px” box_shadow_blur=”60px” box_shadow_color=”rgba(71,74,182,0.12)” locked=”off”]<\/p>\n
P1. Multidimensional Scaling \u2013 P2. Similarities and Dissimilarities \u2013 P3. Unfolding and Other Special Scaling Methods \u2013 P4. Multiway Scaling<\/p>\n
[\/et_pb_blurb][et_pb_blurb title=”Software Developments” url=”#” image=”http:\/\/datascience.unifi.it\/cladag2021\/wp-content\/uploads\/2018\/09\/coding-iconArtboard-19-copy-8.jpg” icon_placement=”left” image_max_width=”64px” content_max_width=”1100px” admin_label=”Chapter” _builder_version=”3.0.82″ header_font=”|on|||” header_text_color=”#2e2545″ header_line_height=”1.5em” body_text_color=”#8585bd” body_font_size=”16px” body_line_height=”1.9em” background_color=”#ffffff” custom_margin=”|||” custom_padding=”30px|40px|30px|40px” animation_style=”zoom” animation_direction=”bottom” animation_intensity_zoom=”20%” animation_starting_opacity=”100%” box_shadow_style=”preset2″ box_shadow_horizontal=”0px” box_shadow_vertical=”0px” box_shadow_blur=”60px” box_shadow_color=”rgba(71,74,182,0.12)” locked=”off”]<\/p>\n
S1. Algorithms for Classification \u2013 S2. Data Visualization \u2013 \u2028S3. Algorithms for Data Analysis<\/p>\n
[\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Conference Themes Contributed papers from scholars and practitioners are invited on any of the topics below as well as on related issues Classification Theory T1. Fuzzy Methods \u2013 T2. Hierarchical Classification \u2013 T3. Non Hierarchical Classification \u2013 T4. Pattern Recognition \u2013 T5.Bayesian Classification \u2013 T6. Classification of Multiway and Functional Data \u2013 T7. Probabilistic Methods […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":""},"_links":{"self":[{"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/pages\/388"}],"collection":[{"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/comments?post=388"}],"version-history":[{"count":18,"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/pages\/388\/revisions"}],"predecessor-version":[{"id":34896,"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/pages\/388\/revisions\/34896"}],"wp:attachment":[{"href":"https:\/\/datascience.unifi.it\/cladag2021\/wp-json\/wp\/v2\/media?parent=388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}