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Classificatore bayesiano - Wikipedia

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.mbox-text-div>div,.mw-parser-output .avviso .mbox-text-full-div>div{font-size:90%}.mw-parser-output .avviso .mbox-image{flex-basis:52px;flex-grow:0;flex-shrink:0}.mw-parser-output .avviso .mbox-text-full-div .hide-when-compact{display:block}</style><div style="" class="ambox metadata noprint plainlinks avviso avviso-generico"> <div class="avviso-immagine mbox-image noprint"><span typeof="mw:File"><a href="/wiki/File:Puzzle_stub.svg" class="mw-file-description" title="Abbozzo"><img alt="Abbozzo" src="//upload.wikimedia.org/wikipedia/commons/thumb/0/0e/Puzzle_stub.svg/45px-Puzzle_stub.svg.png" decoding="async" width="45" height="45" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/0/0e/Puzzle_stub.svg/68px-Puzzle_stub.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/0/0e/Puzzle_stub.svg/90px-Puzzle_stub.svg.png 2x" data-file-width="800" data-file-height="800" /></a></span></div> <div class="avviso-testo mbox-text"> <div class="mbox-text-div"><b>Questa voce &#32;sull'argomento matematica applicata è solo un <a href="/wiki/Aiuto:Abbozzo" title="Aiuto:Abbozzo">abbozzo</a></b>.<br /> <div style="font-size:90%;"><a class="external text" href="https://it.wikipedia.org/w/index.php?title=Classificatore_bayesiano&amp;action=edit">Contribuisci</a> a migliorarla secondo le <a href="/wiki/Aiuto:Manuale_di_stile" title="Aiuto:Manuale di stile">convenzioni di Wikipedia</a>. </div> <div class="hide-when-compact"> </div> </div> </div> </div> <p>Un <b>classificatore <i>bayesiano</i></b> è un <a href="/wiki/Classificatore_(matematica)" title="Classificatore (matematica)">classificatore</a> basato sull'applicazione del <a href="/wiki/Teorema_di_Bayes" title="Teorema di Bayes">teorema di Bayes</a><sup id="cite_ref-duda_1-0" class="reference"><a href="#cite_note-duda-1"><span class="cite-bracket">&#91;</span>1<span class="cite-bracket">&#93;</span></a></sup>. </p><p>Il classificatore <i>bayesiano</i> richiede la conoscenza delle probabilità a priori e condizionali relative al problema, quantità che in generale non sono note ma sono tipicamente stimabili. Se è possibile ottenere delle stime affidabili delle probabilità coinvolte nel teorema, il classificatore <i>bayesiano</i> risulta generalmente affidabile e potenzialmente compatto. Spesso viene detto "classificatore <i>bayesiano</i> completo" (<i>full Bayes classifier</i> o anche <i>belief network</i>). Per costruzione, il classificatore <i>bayesiano</i> minimizza il rischio di classificazione<sup id="cite_ref-duda_1-1" class="reference"><a href="#cite_note-duda-1"><span class="cite-bracket">&#91;</span>1<span class="cite-bracket">&#93;</span></a></sup>. </p><p>Nel gergo della <a href="/wiki/Text_categorization" title="Text categorization">classificazione di testi</a>, con il termine "classificatore <i>bayesiano</i>" ci si riferisce convenzionalmente al cosiddetto "classificatore <i>bayesiano</i> ingenuo" (<i>naïve Bayes classifier</i>)<sup id="cite_ref-duda_1-2" class="reference"><a href="#cite_note-duda-1"><span class="cite-bracket">&#91;</span>1<span class="cite-bracket">&#93;</span></a></sup><sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">&#91;</span>2<span class="cite-bracket">&#93;</span></a></sup>, ossia un classificatore <i>bayesiano</i> semplificato con un modello di <a href="/wiki/Probabilit%C3%A0" title="Probabilità">probabilità</a> sottostante che fa l'ipotesi di <a href="/wiki/Indipendenza_(probabilit%C3%A0)" class="mw-redirect" title="Indipendenza (probabilità)">indipendenza</a> delle <i><a href="/wiki/Caratteristica_(apprendimento_automatico)" title="Caratteristica (apprendimento automatico)">caratteristiche</a></i>, cioè assume che la presenza o l'assenza di un particolare attributo in un documento testuale non è correlata alla presenza o assenza di altri attributi. </p><p>In queste ipotesi semplificate (dette appunto "ingenue", in inglese anche <i>idiot</i>), il modello è realizzabile con molta maggiore facilità. L'esperienza dimostra che il metodo funziona in molti problemi pratici<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">&#91;</span>3<span class="cite-bracket">&#93;</span></a></sup>, come per esempio il filtraggio anti-spam adattivo<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">&#91;</span>4<span class="cite-bracket">&#93;</span></a></sup>. </p> <div class="mw-heading mw-heading2"><h2 id="Note">Note</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Classificatore_bayesiano&amp;veaction=edit&amp;section=1" title="Modifica la sezione Note" class="mw-editsection-visualeditor"><span>modifica</span></a><span class="mw-editsection-divider"> | </span><a href="/w/index.php?title=Classificatore_bayesiano&amp;action=edit&amp;section=1" title="Edit section&#039;s source code: Note"><span>modifica wikitesto</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-references-wrap"><ol class="references"> <li id="cite_note-duda-1"><span class="mw-cite-backlink"><b>^</b> <sup><i><a href="#cite_ref-duda_1-0">a</a></i></sup> <sup><i><a href="#cite_ref-duda_1-1">b</a></i></sup> <sup><i><a href="#cite_ref-duda_1-2">c</a></i></sup></span> <span class="reference-text">Duda, R. O. &amp; P. E. Hart (1973), <i>Pattern Classification and Scene Analysis</i>, New York: John Wiley &amp; Sons</span> </li> <li id="cite_note-2"><a href="#cite_ref-2"><b>^</b></a> <span class="reference-text">Langley, P., W. Iba, &amp; K. Thompson (1992), <i>An analysis of Bayesian classifiers</i>, da <i>Proceedings, Tenth National Conference on Artificial Intelligence</i> (pp. 223–228). Menlo Park, CA: AAAI Press</span> </li> <li id="cite_note-3"><a href="#cite_ref-3"><b>^</b></a> <span class="reference-text">N. Friedman, D. Geiger, &amp; M. Goldszmit (1997), <i>Bayesian Network Classifiers</i>, in <i>Machine Learning</i>, 29, 131–163</span> </li> <li id="cite_note-4"><a href="#cite_ref-4"><b>^</b></a> <span class="reference-text">M. Sahami, S. Dumais, D. Heckerman, E. Horvitz (1998), <i>A Bayesian approach to filtering junk e-mail</i>, AAAI'98 <i>Workshop on Learning for Text Categorization</i></span> </li> </ol></div> <div class="mw-heading mw-heading2"><h2 id="Voci_correlate">Voci correlate</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Classificatore_bayesiano&amp;veaction=edit&amp;section=2" title="Modifica la sezione Voci correlate" class="mw-editsection-visualeditor"><span>modifica</span></a><span class="mw-editsection-divider"> | </span><a href="/w/index.php?title=Classificatore_bayesiano&amp;action=edit&amp;section=2" title="Edit section&#039;s source code: Voci correlate"><span>modifica wikitesto</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Teorema_di_Bayes" title="Teorema di Bayes">Teorema di Bayes</a></li> <li><a href="/wiki/Apprendimento_supervisionato" title="Apprendimento supervisionato">Apprendimento supervisionato</a></li></ul> <style data-mw-deduplicate="TemplateStyles:r141815314">.mw-parser-output .navbox{border:1px solid #aaa;clear:both;margin:auto;padding:2px;width:100%}.mw-parser-output .navbox th{padding-left:1em;padding-right:1em;text-align:center}.mw-parser-output .navbox>tbody>tr:first-child>th{background:#ccf;font-size:90%;width:100%;color:var(--color-base,black)}.mw-parser-output .navbox_navbar{float:left;margin:0;padding:0 10px 0 0;text-align:left;width:6em}.mw-parser-output .navbox_title{font-size:110%}.mw-parser-output .navbox_abovebelow{background:#ddf;font-size:90%;font-weight:normal}.mw-parser-output .navbox_group{background:#ddf;font-size:90%;padding:0 10px;white-space:nowrap}.mw-parser-output .navbox_list{font-size:90%;width:100%}.mw-parser-output .navbox_list a{white-space:nowrap}html:not(.vector-feature-night-mode-enabled) .mw-parser-output .navbox_odd{background:#fdfdfd;color:var(--color-base,black)}html:not(.vector-feature-night-mode-enabled) .mw-parser-output .navbox_even{background:#f7f7f7;color:var(--color-base,black)}.mw-parser-output .navbox a.mw-selflink{color:var(--color-base,black)}.mw-parser-output .navbox_center{text-align:center}.mw-parser-output .navbox .navbox_image{padding-left:7px;vertical-align:middle;width:0}.mw-parser-output .navbox+.navbox{margin-top:-1px}.mw-parser-output .navbox .mw-collapsible-toggle{font-weight:normal;text-align:right;width:7em}body.skin--responsive .mw-parser-output .navbox_image img{max-width:none!important}.mw-parser-output .subnavbox{margin:-3px;width:100%}.mw-parser-output .subnavbox_group{background:#e6e6ff;padding:0 10px}@media screen{html.skin-theme-clientpref-night .mw-parser-output .navbox>tbody>tr:first-child>th{background:var(--background-color-interactive)!important}html.skin-theme-clientpref-night .mw-parser-output .navbox th{color:var(--color-base)!important}html.skin-theme-clientpref-night .mw-parser-output .navbox_abovebelow,html.skin-theme-clientpref-night .mw-parser-output .navbox_group{background:var(--background-color-interactive-subtle)!important}html.skin-theme-clientpref-night .mw-parser-output .subnavbox_group{background:var(--background-color-neutral-subtle)!important}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .navbox>tbody>tr:first-child>th{background:var(--background-color-interactive)!important}html.skin-theme-clientpref-os .mw-parser-output .navbox th{color:var(--color-base)!important}html.skin-theme-clientpref-os .mw-parser-output .navbox_abovebelow,html.skin-theme-clientpref-os .mw-parser-output .navbox_group{background:var(--background-color-interactive-subtle)!important}html.skin-theme-clientpref-os .mw-parser-output .subnavbox_group{background:var(--background-color-neutral-subtle)!important}}</style><table class="navbox mw-collapsible mw-collapsed noprint metadata" id="navbox-Apprendimento_automatico"><tbody><tr><th colspan="3"><div class="navbox_navbar"><div class="noprint plainlinks" style="background-color:transparent; padding:0; font-size:xx-small; color:var(--color-base, #000000); white-space:nowrap;"><a href="/wiki/Template:Apprendimento_automatico" title="Template:Apprendimento automatico"><span title="Vai alla pagina del template">V</span></a>&#160;·&#160;<a href="/w/index.php?title=Discussioni_template:Apprendimento_automatico&amp;action=edit&amp;redlink=1" class="new" title="Discussioni template:Apprendimento automatico (la pagina non esiste)"><span title="Discuti del template">D</span></a>&#160;·&#160;<a class="external text" href="https://it.wikipedia.org/w/index.php?title=Template:Apprendimento_automatico&amp;action=edit"><span title="Modifica il template. 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title="Apprendimento supervisionato">Apprendimento supervisionato</a><b>&#160;·</b> <a href="/wiki/Apprendimento_per_rinforzo" title="Apprendimento per rinforzo">Apprendimento per rinforzo</a><b>&#160;·</b> <a href="/wiki/Apprendimento_profondo" title="Apprendimento profondo">Apprendimento profondo</a></td><td rowspan="8" class="navbox_image"><span typeof="mw:File"><a href="/wiki/File:Kernel_Machine.svg" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/f/fe/Kernel_Machine.svg/150px-Kernel_Machine.svg.png" decoding="async" width="150" height="68" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/f/fe/Kernel_Machine.svg/225px-Kernel_Machine.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/f/fe/Kernel_Machine.svg/300px-Kernel_Machine.svg.png 2x" data-file-width="512" data-file-height="233" /></a></span><br /><br /><span typeof="mw:File"><a href="/wiki/File:Random_forest_model_space.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/a/a7/Random_forest_model_space.png/70px-Random_forest_model_space.png" decoding="async" width="70" height="70" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/a/a7/Random_forest_model_space.png/105px-Random_forest_model_space.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/a/a7/Random_forest_model_space.png/140px-Random_forest_model_space.png 2x" data-file-width="512" data-file-height="512" /></a></span></td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;"><a href="/wiki/Apprendimento_non_supervisionato" title="Apprendimento non supervisionato">Apprendimento non supervisionato</a></th><td colspan="1" class="navbox_list navbox_even"><a href="/wiki/Clustering" title="Clustering">Clustering</a><b>&#160;·</b> <a href="/wiki/Clustering_gerarchico" title="Clustering gerarchico">Clustering gerarchico</a><b>&#160;·</b> <a href="/wiki/K-means" title="K-means">K-means</a><b>&#160;·</b> <a href="/wiki/Algoritmo_EM" title="Algoritmo EM">Algoritmo EM</a><b>&#160;·</b> <a href="/wiki/DBSCAN" title="DBSCAN">DBSCAN</a><b>&#160;·</b> <a href="/wiki/Mean_shift" title="Mean shift">Mean shift</a><b>&#160;·</b> <a href="/wiki/Rete_generativa_avversaria" title="Rete generativa avversaria">Rete generativa avversaria</a> (cGAN<b>&#160;·</b> VAE-GAN<b>&#160;·</b> cycleGAN)</td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;"><a href="/wiki/Apprendimento_supervisionato" title="Apprendimento supervisionato">Apprendimento supervisionato</a></th><td colspan="1" class="navbox_list navbox_odd"><a href="/wiki/Albero_di_decisione" title="Albero di decisione">Albero di decisione</a><b>&#160;·</b> <a href="/wiki/Foresta_casuale" title="Foresta casuale">Foresta casuale</a><b>&#160;·</b> <a href="/wiki/Conditional_random_field" title="Conditional random field">Conditional random fields</a> CRF<b>&#160;·</b> <a href="/wiki/Modello_di_Markov_nascosto" title="Modello di Markov nascosto">Modello di Markov nascosto</a><b>&#160;·</b> <a href="/wiki/K-nearest_neighbors" title="K-nearest neighbors">K-nearest neighbors</a><b>&#160;·</b> <a class="mw-selflink selflink">Classificatore bayesiano</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_artificiale" title="Rete neurale artificiale">Rete neurale artificiale</a><b>&#160;·</b> <a href="/wiki/Regressione_lineare" title="Regressione lineare">Regressione lineare</a><b>&#160;·</b> <a href="/wiki/Modello_logit" title="Modello logit">Regressione logistica</a><b>&#160;·</b> <a href="/wiki/Modello_grafico" title="Modello grafico">Modelli grafici</a><b>&#160;·</b> <a href="/wiki/Macchine_a_vettori_di_supporto" title="Macchine a vettori di supporto">Macchine a vettori di supporto</a></td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;"><a href="/wiki/Apprendimento_per_rinforzo" title="Apprendimento per rinforzo">Apprendimento per rinforzo</a></th><td colspan="1" class="navbox_list navbox_even"><a href="/wiki/Q-learning" title="Q-learning">Q-learning</a><b>&#160;·</b> <a href="/wiki/SARSA" title="SARSA">SARSA</a><b>&#160;·</b> <a href="/wiki/Temporal_difference_learning" title="Temporal difference learning">TD</a></td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;"><a href="/wiki/Riduzione_della_dimensionalit%C3%A0" title="Riduzione della dimensionalità">Riduzione della dimensionalità</a></th><td colspan="1" class="navbox_list navbox_odd"><a href="/wiki/Analisi_fattoriale" title="Analisi fattoriale">Analisi fattoriale</a><b>&#160;·</b> <a href="/wiki/Analisi_della_correlazione_canonica" title="Analisi della correlazione canonica">Analisi della correlazione canonica</a> (CCA)<b>&#160;·</b> <a href="/wiki/Analisi_delle_componenti_indipendenti" title="Analisi delle componenti indipendenti">Analisi delle componenti indipendenti</a> (ICA)<b>&#160;·</b> <a href="/wiki/Analisi_discriminante_lineare" title="Analisi discriminante lineare">Analisi discriminante lineare</a> (LDA)<b>&#160;·</b> <a href="/wiki/Analisi_delle_componenti_principali" title="Analisi delle componenti principali">Analisi delle componenti principali</a> (PCA)<b>&#160;·</b> <a href="/wiki/Selezione_delle_caratteristiche" title="Selezione delle caratteristiche">Selezione delle caratteristiche</a><b>&#160;·</b> <a href="/wiki/Estrazione_di_caratteristiche" title="Estrazione di caratteristiche">Estrazione di caratteristiche</a><b>&#160;·</b> <a href="/wiki/T-distributed_stochastic_neighbor_embedding" title="T-distributed stochastic neighbor embedding">t-distributed stochastic neighbor embedding</a> (t-SNE)</td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;"><a href="/wiki/Rete_neurale_artificiale" title="Rete neurale artificiale">Reti neurali artificiali</a></th><td colspan="1" class="navbox_list navbox_even"><a href="/wiki/Percettrone" title="Percettrone">Percettrone</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_a_base_radiale" title="Rete neurale a base radiale">Rete neurale a base radiale</a><b>&#160;·</b> <a href="/wiki/Rete_bayesiana" title="Rete bayesiana">Rete bayesiana</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_feed-forward" title="Rete neurale feed-forward">Rete neurale feed-forward</a><b>&#160;·</b> <a href="/wiki/Rete_di_Hopfield" title="Rete di Hopfield">Rete di Hopfield</a><b>&#160;·</b> <a href="/wiki/Percettrone_multistrato" title="Percettrone multistrato">Percettrone multistrato</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_ricorrente" title="Rete neurale ricorrente">Rete neurale ricorrente</a> (<a href="/w/index.php?title=Long_short-term_memory&amp;action=edit&amp;redlink=1" class="new" title="Long short-term memory (la pagina non esiste)">LSTM</a>)<b>&#160;·</b> <a href="/wiki/Macchina_di_Boltzmann_ristretta" title="Macchina di Boltzmann ristretta">Macchina di Boltzmann ristretta</a><b>&#160;·</b> <a href="/wiki/Mappa_auto-organizzata" title="Mappa auto-organizzata">Mappa auto-organizzata</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_convoluzionale" title="Rete neurale convoluzionale">Rete neurale convoluzionale</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_a_ritardo" title="Rete neurale a ritardo">Rete neurale a ritardo</a><b>&#160;·</b> <a href="/wiki/Rete_neurale_spiking" title="Rete neurale spiking">Rete neurale spiking</a><b>&#160;·</b> <a href="/wiki/Trasformatore_(informatica)" title="Trasformatore (informatica)">Trasformatore</a></td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;">Software</th><td colspan="1" class="navbox_list navbox_odd"><a href="/wiki/Keras" title="Keras">Keras</a><b>&#160;·</b> <a href="/wiki/Microsoft_Cognitive_Toolkit" title="Microsoft Cognitive Toolkit">Microsoft Cognitive Toolkit</a><b>&#160;·</b> <a href="/wiki/Scikit-learn" title="Scikit-learn">Scikit-learn</a><b>&#160;·</b> <a href="/wiki/TensorFlow" title="TensorFlow">TensorFlow</a><b>&#160;·</b> <a href="/wiki/Theano" title="Theano">Theano</a><b>&#160;·</b> <a href="/w/index.php?title=Torch_(libreria_software)&amp;action=edit&amp;redlink=1" class="new" title="Torch (libreria software) (la pagina non esiste)">Torch</a><b>&#160;·</b> <a href="/wiki/Weka_(software)" title="Weka (software)">Weka</a></td></tr><tr><th colspan="1" class="navbox_group" style="text-align:center;">Altro</th><td colspan="1" class="navbox_list navbox_even"><a href="/wiki/Algoritmo_genetico" title="Algoritmo genetico">Algoritmo genetico</a><b>&#160;·</b> <a href="/wiki/Particle_Swarm_Optimization" title="Particle Swarm Optimization">Particle Swarm Optimization</a><b>&#160;·</b> <a href="/wiki/Caratteristica_(apprendimento_automatico)" title="Caratteristica (apprendimento automatico)">Caratteristica</a><b>&#160;·</b> <a href="/wiki/Compromesso_bias-varianza" title="Compromesso bias-varianza">Compromesso bias-varianza</a><b>&#160;·</b> <a 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