Ukufunda okungagadiwe kuyindlela eyisisekelo kulo mkhakha ubuhlakani bokwenziwa nokufunda ngomshini. Ngokungafani nokufunda okugadiwe, okuncike kudatha enelebula, ukufunda okungagadiwe kugxile ekutholeni amaphethini nezakhiwo kumasethi edatha ngaphandle kokuqondisa kwangaphandle. Le ndlela yokufunda yomshini ivumela imishini ukuthi ifunde ngokuzimela, ihlonze ukuhlobana okufihliwe, futhi ikhiqize ulwazi olubalulekile ngaphandle kwesidingo sempendulo ecacile. Kulesi sihloko, sizohlola ngokujulile ukuthi kuyini ukufunda okungagadiwe nokuthi ukusetshenziswa kwakho kuqhubekisele phambili kanjani inqubekelaphambili ebalulekile emikhakheni eyahlukene, kusukela ekuhlukaniseni idatha kuya ekukhishweni kwezici nokukhiqizwa kokuqukethwe.
1. Isingeniso somqondo wokuFunda okungagadiwe
Ukufunda okungagadiwe igatsha lokufunda komshini eligxile ekutholeni amaphethini afihliwe noma izakhiwo kusethi yedatha ngaphandle kwesidingo samalebula achazwe ngaphambilini noma izigaba. Ngokungafani nokufunda okugadiwe, lapho unesethi yedatha yokufaka kanye nemiphumela oyifunayo, ekufundeni okungagadiwe unedatha yokufaka kuphela. Le ndlela isetshenziswa uma amalebula engatholakali noma uma ufuna ukuhlola ukwakheka nobudlelwano phakathi kwedatha ngendlela engacatshangelwayo.
Enye yezindlela ezivame kakhulu ekufundeni okungagadiwe ukuqoqa noma ukuhlanganisa. Le nqubo ihlose ukuqoqa idatha ngezigaba noma amaqoqo ahlukene ngokusekelwe kokufana kwawo. Ngokuhlanganisa idatha, singathola ulwazi mayelana nesakhiwo esiyisisekelo sedatha futhi sithole ubudlelwano phakathi kwabo. Kunama-algorithms wokuhlanganisa ahlukene, njenge-algorithm ye-K-Means, ukuqoqwana kwe-hierarchical, kanye ne-spectral clustering, phakathi kokunye.
Enye indlela esetshenziswa ekufundeni okungagadiwe ukuncishiswa kobukhulu. Le nqubo ihlose ukunciphisa inani lobukhulu bedatha, kuyilapho kugcinwa ulwazi oluningi lwangempela ngangokunokwenzeka. Lokhu kubaluleke kakhulu uma usebenza namasethi edatha enobukhulu obuphezulu, njengoba kungase kube nzima ukubona ngeso lengqondo nokuhlaziya idatha iyonke. ifomu lokuqala. Ukwehliswa kobukhulu kungasiza ukwenza lula ukuhlaziya idatha futhi kwenze kube lula ukuthola amaphethini noma izakhiwo ezifihliwe kuzo.
2. Incazelo kanye nezici Zokufunda Okungagadiwe
Ukufunda okungagadiwe kuyindlela esetshenziswa emkhakheni we ukuhlakanipha okungekhona okwangempela ebonakala ngokungadingi ukungenelela komphathi wangaphandle phakathi nenqubo yokuqeqesha yemodeli yokufunda yomshini. Ngokungafani nokufunda okugadiwe, lapho amalebula noma amakilasi anikezwa kudatha yokuqeqeshwa, ekufundeni okungagadiwe idatha ayinayo ilebula futhi imodeli kufanele ithole amaphethini afihliwe noma izakhiwo ngokwayo.
Esinye sezici eziyinhloko zokufunda okungagadiwe yi lokho kusetshenziswa lapho idatha yokuqeqeshwa enelebula ingatholakali noma lapho ufuna ukuhlola nokuthola ulwazi olusha kudatha. Le ndlela iwusizo ezinhlelweni eziningi, njengokuhlukaniswa kwekhasimende, ukuhlanganisa amadokhumenti, ukutholwa okudidayo, kanye nokunconywa komkhiqizo.
Kunezindlela ezahlukahlukene zokufunda ezingagadiwe, okugqama kuzo ukuhlanganisa nokuncishiswa kobukhulu. Ukuhlanganisa idatha yamaqembu ibe amasethi noma amaqoqo ngokusekelwe ekufananeni kwawo, kuyilapho ukuncishiswa kobukhulu kudinga ukuthola ukumelela okuhlangene noma okufingqiwe kwedatha, okuqeda izici ezingadingekile noma ezingabalulekile. Lawa maqhinga asivumela ukuthi sithole ukwakheka okuyisisekelo kudatha futhi sikhiphe ulwazi oluwusizo kuyo.
3. Ama-algorithms nezindlela ezisetshenziswa ekuFundeni okungagadiwe
Ukufunda Okungagadiwe igatsha lokufunda komshini elizinikele ekuhlaziyeni nasekuchazeni idatha ngaphandle kwesidingo samalebula angaphambili noma izigaba. Kulesi sigaba, sizohlaziya ama-algorithms nezindlela ezisetshenziswe kulo mkhakha.
Enye yama-algorithms asetshenziswa kakhulu ekufundeni okungagadiwe i Clustering, ehlanganisa izakhi ezifanayo zibe amaqoqo. Ukuqaliswa kwayo kungenziwa ngokusebenzisa ama-algorithms anjengokuthi k-izindlela o DBSCAN. Lawa ma-algorithms adinga ukukhethwa kwenombolo yamaqoqo noma ukubalwa kwamabanga, ngokulandelana. Ngakho-ke, kubalulekile ukuqonda umthelela walezi zinqumo emgqeni ophansi.
Enye indlela esetshenziswa kabanzi yile I-Principal Component Analysis (PCA), esetshenziselwa ukunciphisa ubukhulu bedatha. Ngokusebenzisa i-PCA, kungenzeka ukuthola inhlanganisela yomugqa yeziguquko zangempela ezichaza ukuhlukahluka okukhulu kwedatha. Lokhu kuvumela idatha ukuthi imelelwe endaweni encane yobukhulu, kube lula ukuchazwa kwayo nokuhlaziya.
4. Izinzuzo kanye nokubi kokufunda okungagadiwe
Ukufunda okungagadiwe kunikeza eziningana izinzuzo kanye nokungalungi okubalulekile ukukhumbula lapho usebenzisa le nqubo ku-intelligence yokufakelwa kanye nezinkinga zokufunda ngomshini. Enye yezinzuzo eziyinhloko ikhono layo lokuthola amaphethini nezakhiwo ezifihliwe kumasethi amakhulu wedatha ngaphandle kwesidingo samalebula noma izinkomba zangaphandle. Lokhu kuvumela ukutholwa kolwazi olusha nolubalulekile olungasetshenziswa ukwenza izinqumo, ukuhlukanisa idatha noma ukukhiqiza izethulo ezihlangene. Ukwengeza, ukufunda okungagadiwe kusiza kakhulu ezimweni lapho ingekho khona impendulo “elungile” eyaziwa ngaphambilini, okuyenza ibe ithuluzi elinamandla emisebenzini yokuhlola nokuthola.
Kodwa-ke, kukhona futhi nezinkinga ezihlobene nokufunda okungagadiwe. Ububi obukhulu bulele ekuntulekeni kokulawula nokugada ngesikhathi sokufunda. Njengoba ingekho impendulo "elungile" eyaziwayo, imiphumela etholiwe ingase ingabi wusizo noma ihambisane nenkinga ekhona. Ukwengeza, ukutolika kwemiphumela kungase kube nzima kakhulu ngenxa yokuntuleka kwamamethrikhi enhloso yokuhlola ukusebenza kwe-algorithm.
Okunye okungalungile kokufunda okungagadiwe ukuzwela kwakho kudatha yokufaka. Ama-algorithms wokufunda komshini ongagadiwe angathinteka ngabangaphandle, umsindo, noma ukuhlanekezelwa kwedatha, okungaholela emiphumeleni engalungile noma engalungile. Kubalulekile ukwenza ukuhlaziya ngokucophelela idatha yokufaka nokusebenzisa amasu okucubungula kusengaphambili ukuze unciphise lezi zinkinga. Kafushane, nakuba ukufunda okungagadiwe kunikeza izinzuzo eziningi, kubalulekile futhi ukuqaphela ukulinganiselwa kwakho futhi ucabange ngokucophelela ukuthi Kungcono kakhulu inketho yenkinga ethile okukhulunywa ngayo.
5. Izibonelo zezicelo Zokufunda Okungagadiwe emkhakheni wezobuchwepheshe
Emkhakheni wezobuchwepheshe, Ukufunda Okungagadiwe kufakazele ukuthi kuyithuluzi elibalulekile lezinhlelo zokusebenza ezihlukahlukene. Ngezansi, izibonelo eziphathekayo zokuthi le ndlela isetshenziswa kanjani ezindaweni ezahlukene zobuchwepheshe zizokwethulwa:
1. Ukuhlaziywa Kwedatha: Ukufunda Okungagadiwe kusetshenziswa kakhulu ekuhlaziyeni idatha ukuze kutholwe amaphethini afihliwe nobudlelwano kumasethi amakhulu wedatha. Isibonelo, embonini yokunakekelwa kwezempilo, iqoqo elingagadiwe lingasetshenziswa ukuze kukhonjwe amaqembu eziguli anezici ezifanayo, ezingasiza ekutholeni izifo kusenesikhathi noma ukuhlukaniswa kwabantu ngezinhlelo ezithile zokunakekelwa kwempilo. Ukwengeza, emkhakheni wobunjiniyela, ukuhlaziya okungagadiwe kungasetshenziswa ukukhomba izitayela zokukhiqiza umkhiqizo noma izinqubo zokukhiqiza.
2. Ukucutshungulwa Kwezithombe: Olunye uhlelo oluphawulekayo lokufunda okungagadiwe ukucubungula izithombe. Isibonelo, ama-algorithms okuhlanganisa angagadiwe angasetshenziswa ekuhlukaniseni ngokuzenzakalela isithombe sibe yizifunda ezihlukile noma ukukhomba izinto ezifanayo eqoqweni lezithombe. Lokhu kuwusizo ikakhulukazi ezindaweni ezifana nombono wekhompyutha, amarobhothi noma ukuhlaziya isithombe sezokwelapha.
3. Ukutholwa Okungaqondakali: Ukufunda Okungagadiwe nakho kusetshenziselwa ukutholwa okungaqondakali ezinhlelweni zobuchwepheshe. Ngokwesibonelo, embonini ukuphepha, izindlela zokuthola okudidayo ezingagadiwe zingasetshenziswa ukukhomba ukuziphatha okungajwayelekile kumasistimu okuqapha noma amanethiwekhi okuvikela. Lokhu kukuvumela ukuthi uqaphe ngokuzenzakalela futhi kusenesikhathi mayelana nezinsongo ezingaba khona noma izigameko.
Sengiphetha, Ukufunda Okungagadiwe kunezinhlobonhlobo zezinhlelo zokusebenza emkhakheni wezobuchwepheshe. Kusukela ekuhlaziyweni kwedatha kuya ekucubungulweni kwesithombe kanye nokutholwa okudidayo, le nqubo ifakazela ukuthi iyithuluzi eliguquguqukayo neliwusizo lokuxazulula izinkinga eziyinkimbinkimbi. Amandla okuthola amaphethini afihliwe futhi athole imininingwane ebalulekile kumasethi edatha angabhaliwe enza ukufunda okungagadiwe kube ithuluzi elinamandla ngenkathi yedatha enkulu.
6. Umehluko phakathi kokuFunda okungagadiwe namanye ama-paradigms okufunda komshini
Emkhakheni wokufunda komshini, kunama-paradigm ahlukene asetshenziselwa ukubhekana nezinkinga ngempumelelo. Enye yalezi paradigms aprendizaje no supervisado, ehlukile kwezinye izindlela ezicini ezimbalwa ezibalulekile.
Okokuqala, ngokungafani ukufunda okuqondisiwe, lapho kunezibonelo zokufaka nokuphumayo zokuqeqesha imodeli, ekufundeni okungagadiwe akukho lwazi lwangaphambili olubonisa ukuthi iyini impendulo efanele. Kunalokho, i-algorithm inesibopho sokuthola amaphethini afihliwe noma izakhiwo kudatha ngokwayo.
Omunye umehluko obalulekile utholakala ku- umsebenzi okufanele wenziwe. Nakuba ukufunda okugadiwe kuhloswe ukubikezela umphumela othile ovela kudatha yokufaka, ekufundeni okungagadiwe inhloso eyinhloko ukuthola amaqembu noma izigaba kudatha ngaphandle kokuba nolwazi lwangaphambili ngawo. Amanye amasu asetshenziswa kule ndlela ahlanganisa ukuhlanganisa, ukunciphisa ubukhulu, nokutholwa kokudidayo.
Kafushane, ukufunda okungagadiwe kuyindlela yokufunda komshini esetshenziswa ezimeni lapho izibonelo ezinelebula zingatholakali nalapho lungekho ulwazi lwangaphambili lwezigaba noma izakhiwo ezikhona kudatha. Ngamasu ahlukene, le paradigm ifuna ukuthola amaphethini namaqembu afihliwe kudatha, angasiza ezinhlelweni ezihlukahlukene, njengokuhlaziywa kokumaketha, ukuhlukaniswa kwekhasimende noma ukucubungula izithombe, phakathi kokunye.
7. Izinselelo nobunzima ekuFundeni okungagadiwe
Ukufunda okungagadiwe kuveza uchungechunge lwezinselelo nobunzima obalulekile ukuthi bucatshangelwe lapho kusetshenziswa le nqubo kumaphrojekthi wesayensi yedatha. Ngezansi ezinye zezinselelo ezivame kakhulu nokuthi ungazinqoba kanjani:
1. Ukuntuleka kwamalebula kudatha: Enye yezinselelo ezinkulu zokufunda okungagadiwe ukuntuleka kwamalebula kudatha. Ngokungafani nokufunda okugadiwe, lapho kunedatha enelebula ebonisa impendulo efanele, ekufundeni okungagadiwe idatha ayinakho ukuhlukaniswa kwangaphambili. Lokhu kwenza kube nzima ukuhlola imiphumela futhi kungaholela ekuchazeni okuyiphutha. Ukuze unqobe le nselele, kubalulekile ukusebenzisa amasu okuhlanganisa, njenge-algorithm ye-k-means, ukuqoqa idatha ngezigaba ezifanayo nokwenza lula ukuhlaziya.
2. Ubukhulu obuphezulu bedatha: Enye inselele evamile ekufundeni okungagadiwe ukuphatha amasethi edatha enobukhulu obuphezulu. Uma idatha inokuhlukahluka noma izici eziningi, kungaba nzima ukuthola amaphethini noma izakhiwo ezinengqondo. Ukuze kuxazululwe le nkinga, kunconywa ukwenza ukunciphisa ubukhulu, njengokusebenzisa amasu afana ne-Principal Component Analysis (PCA), evumela okuguquguqukayo okuhambisana kakhulu nokuchazayo ukuthi kukhethwe kusethi yedatha.
3. Ukuhunyushwa kwemiphumela: Inselele yesithathu yokufunda okungagadiwe ilele ekuchazeni imiphumela. Uma usebenzisa amasu okuhlanganisa noma okuthola okudidayo, kungaba nzima ukucacisa incazelo yeqoqo ngalinye noma okutholakele okudidayo. Ngoba xazulula le nkinga, kuphakanyiswa ukuhlola imiphumela ngeso lengqondo kusetshenziswa amagrafu nokubonwayo, kanye nokwenza ukuhlaziya okwengeziwe ukuze kutholakale ubudlelwano obungaba khona noma amaphethini phakathi kwamaqoqo noma okudidayo.
8. Ukuhlolwa kwemiphumela etholwe ngokuFunda okungagadiwe
Okubalulekile ukunquma ukusebenza kahle kanye nekhwalithi yemodeli ekhiqiziwe. Kunamamethrikhi ahlukahlukene namasu avumela ukulinganisa ukusebenza kwama-algorithms nokuqhathanisa amamodeli ahlukene.
Enye yamamethrikhi ajwayeleke kakhulu asetshenziselwa ukuhlola imiphumela yeqoqo Isikolo se-Silhouette. Le metric ibala ukufana kwephoyinti kuqoqo layo uma kuqhathaniswa namanye amaqoqo, ikhiqiza inani eliphakathi kuka- -1 no-1. Inani elisondele ku-1 libonisa ukuthi iphoyinti liseduze neqoqo lalo futhi likude namanye amaqoqo, afiswayo. .
Enye indlela yokuhlola iwukuqinisekisa kwangaphandle, okudinga isethi yedatha yamalebula aziwayo, ukuze kuqhathaniswe imiphumela yemodeli namalebula angempela. Indlela evamile yokwenza lokhu iwukusebenzisa inkomba yeRandi elungisiwe, eqhathanisa amaqoqo akhiqizwa imodeli namalebula aziwayo, okukhiqiza inani eliphakathi kuka-0 no-1. Inani lika-1 libonisa isabelo selebula esiphelele.
9. Ukucubungula ngaphambilini kwedatha ekuFundeni okungagadiwe
Ukucubungula ngaphambilini kwedatha kuyisigaba esibalulekile ekufundeni okungagadiwe, njengoba kunomthelela oqondile kwikhwalithi yemiphumela etholiwe. Kulesi sigaba, izinyathelo ezidingekayo zizoba nemininingwane yokwenza ukucubungula kwangaphambilini okwanele kwedatha ngaphambi kokusebenzisa ama-algorithms okufunda okungagadiwe.
Okokuqala, udinga ukuhlanza idatha. Lokhu kuhlanganisa ukususa amanani angekho, ukulungisa amaphutha, ukususa okuguquguqukayo okungabalulekile, nokubhekana nabangaphandle. Ukuze ukhombe amanani angekho, ungasebenzisa amasu afana nokuhlaziya inani elingekho. Uma sekuhlonziwe, imigqa noma amakholomu anamanani angekho angakhishwa noma amanani angekho angafakwa kusetshenziswa amasu afana nencazelo noma imidiyeni. Ukwengeza, kubalulekile ukulungisa amaphutha kudatha, njengamanani angaphandle kwebanga noma amanani angalungile.
Esinye isinyathelo esibalulekile ekucutshungulweni kwangaphambili kwedatha ukujwayela. Ukujwayela kuhlanganisa ukukala idatha ukuze zonke eziguquguqukayo zibe esikalini esifanayo. Lokhu kubalulekile ngoba ama-algorithms wokufunda amaningi angagadiwe acabanga ukuthi idatha isezingeni elifanayo. Kunezindlela ezihlukile zokujwayela, njengokujwayelekile kwe-min-max kanye ne-z-score normalization. Ukwengeza, kwezinye izimo kungase kudingeke ukuthi kufakwe ikhodi okuguquguqukayo kwezigaba kube okuguquguqukayo kwezinombolo ukuze ama-algorithms akwazi ukusebenza nazo.
10. Ukuhlaziywa kwephethini kanye nokuqoqwa kwedatha ekuFundeni okungagadiwe
Ukuhlaziywa kwephethini kanye nokuqoqwa kwedatha kuyindlela eyinhloko emkhakheni wokufunda okungagadiwe. Le nqubo isivumela ukuthi sithole izakhiwo ezifihliwe nobudlelwano kumasethi wedatha ngaphandle kwesidingo samalebula angaphambilini noma izigaba. Kulokhu okuthunyelwe, sizohlola izindlela namathuluzi ahlukene okwenza lolu hlobo lokuhlaziya nokuhlanganisa, sinikeze indlela Igxathu emvakwe gxathu ukuxazulula inkinga.
Kunamasu amaningana asetshenziswa ekuhlaziyeni amaphethini nasekuhlanganiseni idatha. Ezinye zezindlela ezivame kakhulu zifaka ukuqoqwa kwe-hierarchical, k-means, kanye nokuhlaziywa kwengxenye eyinhloko (PCA). Ngayinye yalezi zindlela inezinzuzo zayo kanye nokubi, ngakho-ke kubalulekile ukuqonda ukuthi iyiphi efaneleka kakhulu esimweni esithile.
Ukuze uqale, kubalulekile ukucubungula kahle idatha ngaphambi kokusebenzisa noma iyiphi indlela yokuhlaziya iphethini nezindlela zokuhlanganisa. Lokhu kuhlanganisa ukwenza imisebenzi efana nokuhlanza idatha, ukwenza kube ngokwejwayelekile, nokukhetha izici ezifanele. Uma idatha isilungisiwe, ungaqhubeka nokusebenzisa amasu okuhlanganisa. Lokhu kungenziwa kusetshenziswa imitapo yolwazi namathuluzi afana ne-scikit-learn ku-Python noma iphakheji ye-Clustering ku-R.
11. Amasu okubona idatha kanye nezindlela zokumelela ekuFundeni okungagadiwe
EkuFundeni Okungagadiwe, omunye wemisebenzi esemqoka wukubona ngeso lengqondo nokumelwa kwedatha. Lawa maqhinga asivumela ukuthi siqonde kangcono amaphethini nezakhiwo ezikhona kumasethi wedatha. Ngezansi amanye amasu namathuluzi angasetshenziselwa le njongo.
Enye yezindlela ezivame kakhulu zokubona idatha ekuFundeni okungagadiwe i-principal component analysis (PCA). Le nqubo ikuvumela ukuthi unciphise ubukhulu bedatha, ugcine ulwazi oluningi ngangokunokwenzeka. Ukusebenzisa i-PCA, amathuluzi afana ne-Python angasetshenziswa nemitapo yolwazi efana ne-scikit-learn. Ngezifundo nezibonelo ezisebenzayo, ungafunda ukuthi ungayisebenzisa kanjani le nqubo futhi ubone ngeso lengqondo imiphumela etholiwe.
Enye indlela ewusizo imephu ye-multidimensional nonlinear (t-SNE). Le nqubo iwusizo ikakhulukazi uma kuziwa ekuboneni idatha ezindaweni ezinobukhulu obuphezulu. I-t-SNE yabela indawo endaweni enezinhlangothi ezimbili kusibonelo ngasinye sedatha, ngenjongo yokulondoloza ubudlelwano bokufana phakathi kwabo. Njenge-PCA, i-t-SNE ingasetshenziswa kusetshenziswa amathuluzi afana nePython nemitapo yolwazi efana ne-scikit-learn. Ngezibonelo nemihlahlandlela yesinyathelo nesinyathelo, ungafunda indlela yokusebenzisa le nqubo yokubonisa idatha ekuFundeni okungagadiwe.
12. Ukufunda Okungagadiwe ekuboneni isithombe nasekucubunguleni inkulumo
Ukufunda okungagadiwe kuyindlela esetshenziswa emkhakheni wokuqashelwa kwesithombe nokucubungula inkulumo esivumela ukuthi sikhiphe amaphethini nezakhiwo ezifihliwe kudatha ngaphandle kwesidingo samalebula noma ulwazi lwereferensi. Le ndlela yokwenza isibe yithuluzi elinamandla kakhulu emkhakheni we ukuhlakanipha okungekhona okwangempela, njengoba ivumela amasistimu ekhompuyutha ukuthi afunde ngokuzenzakalelayo emiqulwini emikhulu yedatha engenamalebula.
Kunezindlela ezihlukahlukene zokufunda ezingagadiwe ezisetshenziswa ekuboneni isithombe nasekucubunguleni inkulumo. Okunye okusetshenziswe kakhulu ukuhlanganisa, ukuncishiswa kobukhulu kanye nokukhiqizwa kwezici. Esimeni sokuqashelwa kwesithombe, lawa masu avumela izithombe ezifanayo ukuthi ziqoqwe ngezigaba noma ukuhlonza izici ezihlukile ezithombeni. Ekucutshungulweni kwenkulumo, ukufunda okungagadiwe kungasetshenziswa ukuhlukanisa nokuhlukanisa amasignali omsindo ngezigaba ezahlukene.
Ukuze usebenzise i-, kuhle ukuthi usebenzise amathuluzi namalabhulali akhethekile ngobuhlakani bokwenziwa, njenge-TensorFlow noma i-scikit-learn. Lawa mamitapo ahlinzeka ngama-algorithm achazwe ngaphambilini asiza ukuqaliswa kwamasu okufunda angagadiwe. Ukwengeza, kunezifundo eziningi nezibonelo eziku-inthanethi ezivumelayo funda isinyathelo ngesinyathelo indlela yokusebenzisa lezi zindlela ezimweni ezingokoqobo. Ngokusebenzisa lawa mathuluzi nezisetshenziswa, kungenzeka ukuthola imiphumela enembile nesebenzayo ekuqapheliseni isithombe nasekucubunguleni inkulumo.
13. Ukuqina nokusebenza kahle kokuFunda okungagadiwe
Lezi yizici ezibalulekile okufanele zicatshangelwe ukuze kuqinisekiswe impumelelo ekusebenziseni le nqubo. Njengoba amasethi edatha ekhula ngosayizi nokuba yinkimbinkimbi, kubalulekile ukuba nezindlela namathuluzi asivumela ukuthi sibhekane nalezi zinselele. ngempumelelo.
Ukuze kuzuzwe ukukala okukhulu Ekufundeni Okungagadiwe, kuyatuseka ukusebenzisa ama-algorithms nezindlela ezikwazi ukusebenza ngamavolumu amakhulu wedatha. Ezinye izibonelo yama-algorithms angakala okufunda okungagadiwe yi MapReduce y Hadoop. Lawa mathuluzi akuvumela ukuthi usabalalise ukucutshungulwa kwedatha kumanodi amaningi, okusheshisa isikhathi sokwenza futhi kukuvumela ukuthi usebenze ngamasethi amakhulu edatha.
Ngokungeziwe ekusebenziseni ama-algorithms angakala, kubalulekile futhi ukuthuthukisa ukusebenza kahle kokucubungula idatha. Ukuze kuzuzwe lokhu, kuyatuswa ukucubungula idatha ngokufanele ngaphambi kokusebenzisa i-algorithm Yokufunda Okungagadiwe. Amanye amasu ajwayelekile okucubungula ngaphambilini afaka ukujwayela kwedatha, ukususwa kwangaphandle, kanye nokwehliswa kobukhulu. Lawa masu avumela ukuqeda umsindo nokuphindaphindeka kwedatha, okubuye kuthuthukise ukusebenza kahle kwe-algorithm.
14. Amathrendi amasha kanye nokuthuthuka kokuFunda okungagadiwe
Emkhakheni Wokufunda Okungagadiwe, amathrendi amasha nentuthuko ihlala ibonwa esivumela ukuthi sithuthukise inqubo yokuhlaziya nokuqonda amanani amakhulu edatha ngaphandle kwesidingo sokulebula mathupha isampula ngayinye.
Enye yezitayela eziphawuleka kakhulu ekufundeni okungagadiwe ukusetshenziswa kwama-algorithms wokuqoqa noma wokuhlanganisa, okuvumela amaphethini namaqembu ukuthi akhonjwe ngaphakathi kwesethi yedatha. Lawa ma-algorithms asebenzisa izindlela zokufunda komshini ukuze ahlukanise amasampula ngezigaba ezihlukene, okwenza kube lula ukuqonda nokukhipha ulwazi olubalulekile.
Ukuze usebenzise ngokugcwele lawa mathrendi amasha, kubalulekile ukucabangela ezinye izincomo. Okokuqala, kubalulekile ukukhetha i-algorithm efanele yokuhlanganisa ngokusekelwe ohlotsheni lwedatha nezinjongo zokuhlaziya. Ngaphezu kwalokho, kuyatuseka ukucubungula idatha ngaphambi kokusebenzisa i-algorithm, ukususa izinto ezingaphandle, ukwenza okuguquguqukayo okujwayelekile nokukhetha okufanele kakhulu. Kuyasiza futhi ukuhlola amapharamitha ahlukene we-algorithm futhi uhlole ukusebenza kwayo ngamamethrikhi afana ne-Silhouette noma Inkomba ye-Calinski-Harabasz.
Sengiphetha, ukufunda okungagadiwe kuyigatsha lokufunda komshini eligxile ekutholeni amaphethini afihliwe nezakhiwo kudatha ngaphandle kokuqondiswa kwamalebula akhona kakade noma izigaba. Ngokusebenzisa ama-algorithms ayinkimbinkimbi, le ndlela isivumela ukuthi sihlole amasethi edatha ngaphandle kwemikhawulo, okuvumela ukutholwa kolwazi olubalulekile nokuqonda okujulile kwedatha.
Ngokungafani nokufunda okugadiwe, ukufunda okungagadiwe akudingi ukugadwa kwangaphambili noma isethi yedatha enelebula, okuyenza ibe indlela ewusizo kakhulu uma lungekho ulwazi lwangaphambili olutholakalayo mayelana nedatha noma lapho sifuna ukuthola amathrendi amasha noma ukuhlobana kumasethi ethu edatha.
Phakathi kwezindlela ezivame ukusetshenziswa ekufundeni okungagadiwe ukuhlanganisa, ukunciphisa ubukhulu, nokuhlotshaniswa kwemithetho. Lezi zindlela zisivumela ukuthi sihlele futhi sibone idatha ngeso lengqondo ngempumelelo kakhudlwana, sihlonze amaqembu afanayo, sithole izici eziphawulekayo, futhi sisungule ubudlelwano phakathi kokuhlukahluka.
Ukufunda okungagadiwe kuyithuluzi elinamandla lokuhlaziya idatha kanye nokukhipha ulwazi emikhakheni eyahlukene, efana nebhayoloji, ezomnotho, ezokwelapha, kanye nobuhlakani bokwenziwa. Ngokusivumela ukuthi sihlole futhi sithole imininingwane ebalulekile ngevolumu enkulu yedatha ngaphandle kwemikhawulo, le ndlela iguqule indlela esibheka ngayo ukuqonda nokuhlaziya idatha. emhlabeni ugesi.
Ngamafuphi, ukufunda okungagadiwe kusinikeza ithuba lokuthola amaphethini afihliwe, izakhiwo nobudlelwano kudatha, sandise ulwazi lwethu futhi sisinikeze imininingwane ebalulekile emikhakheni eyahlukene. Njengoba ingelinye lamagatsha abalulekile okufunda ngomshini, ukufunda okungagadiwe sekuphenduke ithuluzi elibalulekile lanoma yimuphi umuntu noma inkampani efuna ukusebenzisa ngokugcwele amasethi ayo edatha futhi ithole inzuzo yokuncintisana emhlabeni wanamuhla oqhutshwa idatha.
Ngingu-Sebastián Vidal, unjiniyela wekhompyutha ozifelayo ngobuchwepheshe kanye ne-DIY. Ngaphezu kwalokho, ngingumdali we tecnobits.com, lapho ngabelana khona ngezifundo zokwenza ubuchwepheshe bufinyeleleke kakhudlwana futhi buqonde wonke umuntu.