Menene Algorithm Mai Tsari?

A fagen ilimin data y hankali na wucin gadi, ɗaya daga cikin mahimman ra'ayoyin don nazarin ƙirar ƙira da tattara bayanai shine algorithm na Hierarchical Clustering. Wannan hanya, bisa ka'idodin lissafi da ƙididdiga, tana ba da damar tsara tsarin lura zuwa ƙungiyoyi daban-daban ko gungu a cikin tsarin tsari, yana ba da cikakken ra'ayi game da alaƙar da ke tsakanin bayanai. A cikin wannan labarin, za mu bincika zurfin menene Hierarchical Clustering algorithm, yadda ake aiwatar da shi da menene manyan aikace-aikacensa da fa'idodinsa a fagen ilimin kimiyyar bayanai.

1. Gabatarwa zuwa ga tsarin tari algorithm

Algorithm na tari mai matsayi dabara ce ta haɗawa da ke neman raba saitin bayanai zuwa ƙananan ƙungiyoyi masu kama da juna. Wannan algorithm ya dogara ne akan ra'ayin gina tsarin gungu, inda kowane gungu yana haɗuwa da sauran gungu iri ɗaya har sai an samar da gungu guda ɗaya wanda ya ƙunshi dukkan bayanai.

Babban fa'idar tari na matsayi shine cewa ba kwa buƙatar sanin tun da farko adadin gungu da kuke son samu, tunda algorithm yana gina matakan gungu ta atomatik. Bugu da ƙari, yana ba ku damar duba sakamakon ta hanyar hoto kuma ku fahimci tsarin bayanan.

Akwai manyan hanyoyi guda biyu zuwa ga tari na matsayi: agglomerative da rarraba. A cikin tsarin haɓakawa, kuna farawa da ƙungiyoyi guda ɗaya kuma ku haɗa tari mai kama da juna har sai kun sami gungu guda ɗaya wanda ya ƙunshi duk bayanai. A gefe guda kuma, a cikin tsarin rarrabawa, kuna farawa da gungu guda ɗaya wanda ke ɗauke da duk bayanai kuma ku raba shi akai-akai zuwa ƙanana da kamanni.

Don aiwatar da algorithm na gungu na matsayi, ya zama dole a ayyana ma'aunin kamanni tsakanin bayanan. Wannan ma'auni na iya bambanta dangane da nau'in bayanan da ake tantancewa. Wasu matakan gama gari sun haɗa da nisan Euclidean, nisan Manhattan, da nisan daidaitawa. Da zarar an ayyana ma'aunin kamanni, za'a iya amfani da algorithm irin su Ward's, cikakken matsakaita, ko matsakaici mai sauƙi don gina manyan matsayi.

A taƙaice, algorithm ɗin tari na matsayi kayan aiki ne mai ƙarfi don nazarin saitin bayanai da nemo nau'ikan sifofi iri ɗaya. Hanyarsa ta ta'azzara ko rarrabuwar kawuna da ma'anar ma'aunin kamanceceniya sune mahimman abubuwan aiwatarwa. Wannan algorithm yana da amfani musamman lokacin da ba a san adadin gungu da ake so ba kuma ana neman wakilci na gani na sakamakon da aka samu. Koyi yadda ake amfani da algorithm na gungu na matsayi kuma gano yadda ake rukuni bayananku ta hanya mai inganci!

2. Mahimman ra'ayoyi a cikin algorithm na tari na matsayi

3. Nau'o'in gungun algorithms masu matsayi

Akwai daban-daban da ake samu don bayanan rukuni bisa kamanceceniyarsu. Ana iya rarraba waɗannan algorithms zuwa manyan nau'i biyu: agglomerative da rarraba.

Algorithms na Agglomerative suna farawa ta hanyar sanya kowane abu na bayanai zuwa rukuninsa sannan kuma a hankali ya haɗa ƙungiyoyin har sai rukuni ɗaya ya haɗa da duk bayanan. A kowane mataki na haɗawa, ana ƙididdige ma'aunin kamanni tsakanin ƙungiyoyi kuma ana yanke shawarar waɗanda yakamata a haɗa su. Wannan ma'auni na kamanni na iya zama nisa tsakanin centroids na ƙungiyoyi ko nisa tsakanin wuraren mafi kusa na ƙungiyoyi.

A gefe guda, algorithms masu rarraba suna farawa da rukuni ɗaya wanda ke ɗauke da duk bayanai sannan kuma a raba wannan rukunin zuwa ƙananan ƙungiyoyi. A cikin kowane matakin tsagawa, ana zaɓar ƙungiyar da ke akwai kuma an ware su zuwa sabbin ƙungiyoyi biyu. Ana yin wannan rarrabuwa bisa ma'aunin kamanceceniya tsakanin maki a cikin rukunin.

4. Abũbuwan amfãni da rashin amfani na ma'auni na gungu na matsayi

Algorithm na tari na matsayi wata dabara ce da ake amfani da ita sosai don tara bayanai iri ɗaya zuwa rukuni ko tari. Ɗaya daga cikin manyan fa'idodinsa shi ne cewa ba lallai ba ne a ƙididdige yawan adadin da ake so a gaba, tun da algorithm ya haifar da tsarin matsayi wanda za'a iya fassara shi a matakai daban-daban na daki-daki. Wannan yana ba da damar fahimtar tsarin bayanai kuma yana sa ya fi sauƙi don nazari.

Wani muhimmin fa'ida na gunguwar algorithm shine ikonsa na sarrafa nau'ikan bayanai daban-daban, kamar mabambantan ƙididdiga ko ƙididdiga. Wannan ya sa ya zama kayan aiki mai mahimmanci wanda za'a iya daidaita shi zuwa matsaloli daban-daban da saitin bayanai. Bugu da ƙari, algorithm yana da sauƙin aiwatarwa kuma baya buƙatar adadi mai yawa na saitunan sigina.

A gefe guda, rashin lahani na gunguwar tsarin juzu'i shine mafi girman hadaddun lissafin sa idan aka kwatanta da sauran tarin algorithms, musamman lokacin aiki tare da manyan saitin bayanai. Bugu da ƙari, saboda yanayin matsayi na algorithm, yana iya zama da wahala a tantance mafi kyawun adadin tari ko fassara sakamakon a wasu lokuta. Har ila yau, yana da mahimmanci a lura cewa algorithm na iya zama mai kula da bayanan waje ko hayaniya, wanda zai iya rinjayar ingancin gungu da aka samar.

5. Muhimman matakai a cikin aiwatar da algorithm na tari na matsayi

Hanyar 1: Ma'anar matsalar da zaɓin bayanan shigarwa. Mataki na farko na aiwatar da tsarin tari na algorithm shine fahimtar a sarari matsalar da muke ƙoƙarin warwarewa. Dole ne mu gano nau'in bayanan da za mu yi amfani da su kuma mu zaɓi waɗanda suka dace da matsalarmu. Yana da mahimmanci a yanke shawarar abin da halaye na bayanan za a yi la'akari da su a cikin tsarin tarawa.

Hanyar 2: Ana aiwatar da bayanai. Kafin yin amfani da algorithm na gungu na matsayi, ya zama dole a yi wasu ayyukan sarrafa bayanai. Wannan ya haɗa da tsaftace bayanan don cire duk wani hayaniya ko abin da zai iya shafar sakamakon tari na ƙarshe. Hakanan abu ne gama gari don auna bayanai don tabbatar da cewa duk fasalulluka suna da nauyi iri ɗaya kuma guje wa son zuciya a cikin tsarin tari.

Hanyar 3: Zaɓin awo na nisa da hanyar haɗawa. A cikin aiwatar da algorithm na tari na matsayi, dole ne mu zaɓi ma'aunin tazara mai dacewa don auna kamanceceniya tsakanin abubuwa a cikin saitin bayanan mu. Akwai zaɓuɓɓuka da yawa da ake samu, kamar nisan Euclidean, nisan Manhattan, ko tazarar daidaitawa. Bugu da kari, muna buƙatar zaɓar hanyar haɗin kai don haɗa gungu a kowane mataki na algorithm, kamar cikakken hanyar hanyar haɗin gwiwa ko matsakaicin hanyar haɗin gwiwa.

6. Ma'auni na nisa da aka yi amfani da su a cikin algorithm na tari na matsayi

Algorithm na tari na matsayi wata dabara ce da ake amfani da ita don tara bayanai zuwa gungu ko ƙungiyoyi bisa kamancen halaye tsakanin wuraren bayanai. Don ƙayyade kamance tsakanin wuraren bayanai, ya zama dole a yi amfani da ma'aunin nisa. Waɗannan ma'auni suna ƙididdige nisa tsakanin wuraren bayanai kuma ana amfani da su don auna kamanni a cikin tsarin gungu.

Akwai da yawa, wanda ke nuna mafi yawan al'ada kamar:

• Nisan Euclidean: Yana ƙididdige nisa tsakanin wuraren bayanai biyu a cikin sararin Euclidean. Wannan ma'aunin ya dace da ci gaba da bayanan lambobi kuma yana ƙoƙarin ba da ingantaccen sakamako a mafi yawan lokuta.
• Distance Manhattan: Wanda kuma aka sani da nisan birni, yana ƙididdige nisa tsakanin wuraren bayanai biyu ta ƙara cikakkiyar bambance-bambance tsakanin haɗin gwiwar su. Wannan ma'auni ya dace da bayanan da ba na ci gaba ba ko na musamman.
• Nisa mai alaƙa: Yana auna kamanceceniya tsakanin wuraren bayanai guda biyu ta amfani da ma'aunin daidaitawar ƙididdiga. Wannan ma'aunin yana da amfani yayin aiki tare da ƙididdiga bayanai ko bayanai a cikin nau'in tebur na mitar.

Zaɓin ma'aunin nisa da ya dace ya dogara da nau'in bayanai da tsarin matsalar kanta. Yana da mahimmanci a zaɓi ma'auni wanda ya dace da halayen bayanan kuma yana haifar da sakamako mai ma'ana a cikin mahallin matsalar da za a warware. Gwaji tare da ma'aunin nisa daban-daban na iya taimakawa nemo mafi dacewa ga takamaiman matsalar tari mai matsayi.

7. Kimanta ingancin gungu a cikin algorithms na gungu na matsayi

Ƙididdiga ingancin tari wani muhimmin mataki ne a cikin nazarin bayanai ta amfani da algorithms na gungu na matsayi. Don tantance tasirin waɗannan algorithms, ya zama dole a yi amfani da ma'auni na kimantawa waɗanda ke ƙididdige yadda aka haɗa bayanai zuwa gungu daban-daban.

Ɗayan mafi yawan ma'auni da ake amfani da su don kimanta ingancin tari shine haɗin silhouette. Wannan ƙayyadaddun ƙayyadaddun bayanai yana haɗa bayanai game da kamanceceniya ta intra-cluster da rashin kamanceceniya tsakanin gungun don sanya ƙima tsakanin -1 da 1 ga kowane ma'aunin bayanai. Ƙimar da ke kusa da 1 tana nuna kyakkyawar tari, yayin da kimar da ke kusa da -1 ke nuna cewa za a iya sanya ma'aunin bayanai zuwa wani gungu.

Wani ma'auni mai amfani shine Dunn index, wanda ke auna rarrabuwa tsakanin gungu da ƙarancin kowane gungu. Ƙimar mafi girma na jigon Dunn yana nuna ingantacciyar ingancin tari. Bugu da ƙari ga waɗannan ma'auni, yana da mahimmanci don ganin sakamako na gungu na matsayi ta amfani da kayan aiki irin su dendrograms da tarwatsawa don fahimtar tsarin bayanai da kuma rarraba gungu.

8. Misalai na aikace-aikace na gungu na algorithm a fagage daban-daban

Ana amfani da algorithm ɗin tari mai matsayi a ko'ina a fagage daban-daban don tara bayanai iri ɗaya da kuma nazarin alamu. Yanzu sun gabatar Wasu misalai na aikace-aikace masu amfani na algorithm a wurare daban-daban:

1. Magani: Ana amfani da gungu na matsayi a cikin magani don gano nau'ikan cututtuka daban-daban ko cuta ta hanyar nazarin bayanan asibiti da kwayoyin halitta. Misali, wannan algorithm na iya gano ƙungiyoyin masu fama da cutar kansa waɗanda ke amsa daidai da wani magani, yana ba da damar kulawar likita don keɓantawa da haɓakawa.

2. Talla: A fagen tallace-tallace, ana amfani da tari mai matsayi don rarraba abokan ciniki zuwa ƙungiyoyi masu kama da juna dangane da halayen siyensu, abubuwan da suka fi so ko halayen alƙaluma. Ta wannan hanyar, kamfanoni za su iya daidaita dabarun tallan su kuma suna ba da keɓaɓɓen tayi ga kowane ɓangaren abokin ciniki, haɓaka tasirin tallan tallace-tallace.

3. Bioinformatics: A cikin bioinformatics, ana amfani da gungu na matsayi don nazarin jerin DNA ko furotin. Wannan Algorithm yana taimakawa wajen gano rukuni na jerin jerin abubuwa, samar da fahimta cikin aikin da kuma juyin halitta na Biomeolecules. Bugu da ƙari, ana amfani da tari mai matsayi don rarraba kwayoyin halitta zuwa bayanan martaba da kuma nazarin martanin kwayoyin halitta zuwa yanayi daban-daban ko yanayi.

A taƙaice, ana amfani da algorithm na tari mai matsayi a fannoni daban-daban kamar magani, tallace-tallace, da bioinformatics. Ƙarfinsa na haɗa bayanai iri ɗaya da gano alamu ya tabbatar da yana da matuƙar amfani wajen nazarin bayanai a wurare daban-daban. Ko don inganta jiyya, daidaita dabarun talla, ko fahimtar rayayyun halittu, wannan algorithm yana ba da kayan aiki mai ƙarfi don ganowa da nazarin ƙungiyoyin bayanai.

9. Kwatanta tsakanin manyan algorithms na tari da sauran hanyoyin tari

Matsakaicin tari wata shahararriyar hanya ce da ake amfani da ita don tara abubuwa iri ɗaya zuwa rukuni, dangane da kamannin halayensu. Ko da yake akwai wasu hanyoyin tarawa da ake da su, irin su K-means ko DBSCAN, tsarin tari yana da wasu fa'idodi da rashin amfanin da ke sa ta fice. Kwatanta tsakanin waɗannan algorithms zai ba mu damar fahimtar wace hanya ce ta fi dacewa da bayananmu da matsalar da muke son warwarewa.

Daya daga cikin manyan bambance-bambance tsakanin tari mai matsayi da sauran hanyoyin haɗin kai shine hanyar da ake samar da ƙungiyoyi. Yayin da K-ma'ana ko DBSCAN ke sanya kowane abu zuwa rukuni ɗaya, haɗaɗɗen matsayi yana ba da damar kafa ƙungiyoyin gida ko ƙungiyoyi cikin manyan ƙungiyoyi. Wannan na iya zama da amfani idan bayananmu suna da tsari na matsayi ko kuma lokacin da muke son samun cikakken ra'ayi game da alaƙa tsakanin abubuwa.

Wani muhimmin bambanci shine adadin ƙungiyoyin da aka samar. A cikin rarrabuwar kawuna, ba lallai ba ne a fayyace adadin ƙungiyoyi kafin gudanar da algorithm, tunda yana haifar da cikakken matsayi na duk abubuwa. A gefe guda, a cikin hanyoyin kamar K-ma'anar, a baya ya zama dole a bayyana adadin ƙungiyoyin da ake so. Wannan na iya zama matsala idan ba mu san tabbas ko ƙungiyoyi nawa ya kamata a kafa ba. Koyaya, tari mai matsayi yana buƙatar ƙarin lokacin aiwatarwa saboda kamanceceniya tsakanin duk nau'ikan abubuwa dole ne a ƙididdige su.

10. Kayan aiki da dakunan karatu akwai don aiwatar da algorithm na tari na matsayi

Akwai da yawa, ba da damar masu bincike da masu haɓakawa su sami zaɓuɓɓuka masu yawa don aiwatar da wannan nau'in bincike. A ƙasa akwai wasu daga cikin waɗanda aka fi amfani da su da kuma rubuce-rubuce masu kyau:

1. Scikit-koyi: Wannan ɗakin karatu na koyon injin na Python babban zaɓi ne don aiwatar da tsarin tari na algorithm. Yana ba da nau'ikan algorithms na tari iri-iri, gami da gungu na matsayi na agglomerative. Cikakkun takaddun sa da kuma jama'ar masu amfani masu aiki sun sa ya zama abin dogaro da sauƙin amfani.

2. SciPy: Wannan ɗakin karatu na Python yana ba da kewayon kayan aikin kimiyya da algorithms, gami da tari mai matsayi. Yana ba da ayyukan tari kamar haɗin gwiwa () da dendrogram (), waɗanda ke sa aiwatar da algorithm mai sauƙi da inganci. Takaddun SciPy suna da kyau kuma suna ba da koyawa mataki zuwa mataki da misalan yadda ake amfani da waɗannan ayyuka.

3. A: R shine yaren shirye-shirye da aka yi amfani da shi sosai wajen ƙididdiga da nazarin bayanai. Yana da fakiti da yawa da ake samu don tari, kamar fakitin 'cluster' da kunshin 'dendextend'. Waɗannan fakitin suna ba da ayyuka iri-iri da kayan aiki don aiwatar da algorithm, da cikakkun takardu da cikakkun bayanai.

11. Aikace-aikace masu amfani na tsarin tari na algorithm a cikin nazarin bayanai

Algorithm na tattara bayanai ana amfani da shi sosai a cikin nazarin bayanai saboda aikace-aikacen sa a fagage daban-daban. Ta wannan algorithm yana yiwuwa a haɗa abubuwa ko samfurori zuwa rukuni ko gungu, dangane da kamanceceniya da bambance-bambancen su. Wannan nau'in tari yana ba da damar hangen nesa sosai na tsarin bayanai kuma yana taimakawa gano ɓoyayyun alamu da alaƙa.

Una na aikace-aikace Mafi yawan amfani da algorithm ɗin gungu na matsayi yana cikin rarrabuwar abokin ciniki. Ana amfani da shi don haɗa abokan ciniki zuwa rukuni daban-daban dangane da halayensu, halaye ko abubuwan da suke so. Wannan yana ba kamfanoni cikakken ra'ayi game da tushen abokan cinikin su kuma yana ba su damar tsara dabarun tallan masu inganci.

Bugu da ƙari, ana amfani da algorithm ɗin gungu na matsayi a cikin nazarin hoto da ilimin genomics. A cikin nazarin hoto, ana amfani da shi don haɗa hotuna iri ɗaya zuwa rukuni, yana sauƙaƙa bincike da rarraba hotuna. A cikin kwayoyin halitta, ana amfani da shi don rukuni na kwayoyin halitta ko samfurori na halitta bisa ga bayanin jinsin su, yana taimakawa wajen gano alamun da ke hade da takamaiman cututtuka ko yanayi.

12. Iyakoki da la'akari a cikin yin amfani da algorithm na gungu na matsayi

Algorithm na tari na matsayi wata dabara ce da aka yi amfani da ita sosai wajen nazarin bayanai don gano ƙungiyoyi ko tari a cikin saitin bayanai. Duk da haka, yana da mahimmanci a kiyaye wasu iyakoki da la'akari yayin amfani da wannan algorithm.

Iyaka gama gari na tari shine cewa yana iya yin tsadar lissafi akan manyan saitin bayanai. Wannan saboda algorithm yana buƙatar maimaita lissafin nisa tsakanin duk nau'ikan maki a cikin saitin bayanai. Sabili da haka, yana da kyau a yi amfani da wannan algorithm akan ƙananan saitin bayanai ko amfani da dabarun ingantawa don inganta ƙwarewar lissafi.

Wani muhimmin abin la'akari shine zaɓin hanyar haɗin kai da aka yi amfani da shi a cikin ma'auni na tari. Hanyar hanyar haɗi tana ƙayyade yadda ake ƙididdige nisa tsakanin ƙungiyoyi a kowane mataki na algorithm. Akwai hanyoyin haɗin kai daban-daban da ake samu kamar cikakken haɗin kai, matsakaita haɗin kai, da haɗin kan Ward, da sauransu. Yana da mahimmanci a fahimci halaye na kowace hanya kuma zaɓi mafi dacewa don saitin bayanai da makasudin bincike.

13. Sabbin sabbin abubuwa da ci gaban da aka samu a fagen tarukan matsayi

A fannin hada-hadar manyan mukamai, an samu gagarumin ci gaba a 'yan shekarun nan. Waɗannan sabbin abubuwa sun ba mu damar inganta daidaito da ingancin wannan hanyar tattara bayanai. Ɗaya daga cikin manyan sabbin abubuwa shine haɓakar sauri da ƙarfi algorithms waɗanda zasu iya ɗaukar manyan saitin bayanai. Waɗannan algorithms suna amfani da ingantaccen haɓakawa da dabarun daidaitawa don haɓaka aikin tari.

Wata muhimmiyar bidi'a ita ce haɗa mafi ƙaƙƙarfan matakan kamanni a cikin lissafin nisa tsakanin abubuwa. Wannan ya ba mu damar samun ingantattun ƙungiyoyi ta hanyar la'akari ba kawai nisan Euclidean ba, har ma da wasu matakan kamar kamannin cosine ko haɗin Pearson. Bugu da ƙari, an ba da shawarar hanyoyin zaɓi na atomatik na matakan kamanni, wanda ke sauƙaƙe aikace-aikacen su ba tare da buƙatar ilimi na musamman ba.

Hakazalika, an ƙirƙiro hanyoyin da ke haɗa tari tare da wasu dabarun koyo na inji, kamar rage girma ko daidaita ma'aunin algorithm. Wannan yana ba da damar samun ƙarin ƙungiyoyi masu dacewa don nau'ikan bayanai daban-daban da wuraren aikace-aikacen. Bugu da ƙari, an ƙirƙira kayan aikin software da ɗakunan karatu waɗanda ke sauƙaƙe aiwatarwa da kimantawa na gunguwar algorithms na matsayi, wanda ya ba da gudummawa ga yada su da karɓuwa a cikin al'ummar kimiyya.

14. Ƙarshe akan ma'auni na gungu na matsayi

A taƙaice, algorithm na tari na matsayi dabara ce ta haɗawa da ake sanya abubuwa iri ɗaya cikin rukuni. A cikin wannan sashe, mun bincika wannan algorithm cikin zurfi da aikace-aikacen sa.

Ɗaya daga cikin fitattun abubuwan da ke tattare da tsarin gungu na algorithm shine iyawarsa don ƙirƙirar tsari mai matsayi na gungu, wanda ke ba da damar fahimtar bayanai da alaƙa. Wannan hanyar kuma tana ba da sassauci, yana ba da damar raba gungu ko haɗa su kamar yadda ake buƙata.

Bugu da ƙari, mun ga cewa akwai manyan hanyoyi guda biyu a cikin ma'auni na gungu na matsayi: tari mai ƙarfi da tari mai rarrabawa. Duk hanyoyin biyu suna da nasu fa'ida da rashin amfani, kuma zaɓin da ke tsakanin su ya dogara ne akan bayanai da manufofin bincike.

A ƙarshe, algorithm na tari mai matsayi dabara ce ta haɗawa da ke ba da damar tsara saitin bayanai a cikin hanyar bishiya mai matsayi. Ana amfani da wannan nau'in algorithm a wurare daban-daban, kamar hakar bayanai, bioinformatics da ilimin artificial, da sauransu.

Ta hanyar tsarin tara bayanai, ana tattara bayanai gwargwadon kamanninsu ko nisa, suna samar da tsari mai matsayi wanda zai ba da damar alakar da ke tsakanin ƙungiyoyi daban-daban. Wannan yana da amfani musamman don fahimtar ainihin tsarin bayanai da gano ɓoyayyun alamu ko nau'ikan.

Akwai manyan hanyoyi guda biyu a cikin tsarin tari na algorithm: agglomerative da rarrabuwa. A cikin hanyar haɓakawa, ana tattara bayanai suna farawa da abubuwa ɗaya kuma a haɗe su a hankali har sai an kai ƙungiya ɗaya. A daya bangaren kuma, tsarin raba kan yana farawa ne daga kungiya daya ta raba shi zuwa kananan kungiyoyi.

Ya kamata a lura cewa zaɓin hanyar haɗin kai, wanda ke ƙayyade yadda ake ƙididdige kamance tsakanin ƙungiyoyi, yana da mahimmanci don samun ingantacciyar sakamako a cikin tari. Hanyoyin da aka fi sani sun haɗa da cikakken haɗin gwiwa, matsakaicin haɗin gwiwa, da haɗin gwiwar Ward.

Bugu da ƙari, yana da mahimmanci a yi la'akari da ma'aunin nisa da aka yi amfani da shi lokacin ƙididdige kamance tsakanin abubuwa. Wasu matakan nesa da aka fi amfani dasu sune Euclidean, Manhattan da matakan daidaitawa.

A taƙaice, algorithms na gungu na matsayi kayan aiki ne masu mahimmanci a cikin nazarin bayanai. Suna ba da damar haɗa bayanai cikin matsayi, suna bayyana tsarin da ke ƙasa da sauƙaƙe gano alamu da nau'ikan. Amfani da shi ya fadada zuwa wurare daban-daban kuma zaɓin da ya dace na hanyar hanyar haɗin gwiwa da ma'aunin nesa yana da mahimmanci don samun ingantaccen sakamako mai ma'ana.