He algorithm hoʻokaʻawale He mea hana koʻikoʻi ia ma ke kahua o ka aʻo ʻana i ka mīkini a me ka naʻauao artificial. ʻO kāna hana nui ke kālailai ʻikepili, identificar patrones a hāʻawi i nā mea hoʻokahi i categorías predefinidas. Hoʻohana nui ʻia kēia mau algorithm ma nā ʻano āpau, e like me ka ʻike ʻana o spam, mahele clientes, hōʻoia kino a me ka ʻike ʻana o nā kiʻi.
He aha ka algorithm classification?
ʻO nā algorithms hoʻohālikelike he ʻano o ʻano hoʻohālike mālama ʻia i loko o ke aʻo ʻana i ka mīkini. ʻO ia ke kumu e koi ai lākou i kahi pūʻulu o nā ʻikepili i hōʻailona mua ʻia e aʻo a hana. predicciones. ʻO kāna kumu, ʻo ia ka puʻunaue ʻana i nā ʻikepili i nā papa like ʻole a i ʻole nā waeʻano ma o ka nānā ʻana patrones a me nā pilina ma ka ʻikepili aʻo.
No ka laʻana, hiki i kahi algorithm hoʻohālikelike ke kālailai i nā leka uila, ʻike i kekahi nā huaʻōlelo koʻikoʻi o kiʻi kikokikona, a hoʻokaʻawale iā lākou ma ke ʻano he "spam" a "ʻaʻole spam." ʻO kekahi hihia maʻamau i ka maʻi maʻi, kahi e hiki ai i kahi algorithm ke hoʻomaopopo inā loaʻa kahi maʻi i kekahi maʻi e pili ana sintomas previos.
ʻO nā ʻano nui o ka hoʻonohonoho algorithms
Nui nā ʻano o ka hoʻokaʻawale ʻana i nā algorithm, kēlā me kēia me nā hiʻohiʻona kūʻokoʻa e kūpono ai iā lākou no kekahi mau pilikia:
- Nā papa helu laina: Aia kēia ʻano i nā hiʻohiʻona e like me ka logistic regression a me nā mīkini vector kākoʻo (SVM). ʻO kāna hiʻohiʻona nui ka hiki ke hoʻokaʻawale i nā ʻikepili i nā papa like ʻole me ka hoʻohana ʻana i kahi palena a i ʻole hyperplane maikaʻi loa.
- Árboles de decisión: He mau hale ʻikepili hierarchical lākou e hoʻokaʻawale i ka ʻikepili i hoʻonohonoho ʻia i nā subset e pili ana i condiciones específicas. Akaka a maʻalahi lākou e wehewehe.
- Random Forest: ʻO kahi mana hou o nā lāʻau hoʻoholo, hoʻohui ia i nā kumulāʻau he nui e hoʻomaikaʻi i ka pololei del modelo.
- Redes neuronales: Hoʻohana ʻia i nā pilikia paʻakikī, hoʻohālikelike kēia mau pūnaewele i ka hana o ka cerebro humano e ʻike i nā ʻano laina ʻole.
- K-Nearest Neighbors (KNN): Hoʻokaʻawale i ka ʻikepili ma muli o cercanía i nā kiko kokoke loa i ka hakahaka hiʻona.
Nā noi maoli o ka hoʻonohonoho algorithms
Loaʻa i nā algorithms classification nā noi kūpono i nā ʻāpana like ʻole:
- Detección de spam: Hoʻohana nā kānana leka uila i nā algorithm hoʻokaʻawale e nānā i ka mensajes a e hoʻoholo inā he spam lākou a ʻaʻole paha.
- Diagnóstico médico: Kōkua lākou i ka ʻike enfermedades ma muli o nā hōʻailona, ka ʻikepili lapaʻau a me ka mōʻaukala olakino.
- Reconocimiento de imágenes: Hoʻokaʻawale i nā kiʻi i nā papa like personas, nā mea o animales i nā noi e like me ka hōʻailona kiʻi ʻakomi.
- Análisis de sentimientos: Hoʻokaʻawale lākou i nā manaʻo a i ʻole nā manaʻo ma ke ʻano he maikaʻi, ʻino a kū ʻole paha ma muli o kā lākou ʻike.
Nā ʻokoʻa ma waena o ka hoʻokaʻawale ʻana a me ka regression
Hoʻopili pinepine ʻia ka hoʻokaʻawale ʻana me regresión. ʻOiai e nānā ʻia nā ʻano algorithm ʻelua, lawelawe lākou i nā kumu like ʻole:
- Clasificación: Predice nā lepili makaʻala. No ka laʻana, e hoʻoholo ana inā kūʻai ka mea kūʻai aku i kahi huahana (ʻae a ʻaʻole paha).
- Regresión: Predice mau waiwai mau. No ka laʻana, ke koho ʻana i ka nui o nā huahana a ka mea kūʻai aku e kūʻai ai.
ʻO kahi laʻana kūpono ke wānana inā e nānā ke kanaka i kahi kiʻiʻoniʻoni (helu helu) me ka nui o nā manawa a lākou e nānā ai (regression).
ʻO ka mea nui o ke koho ʻana i ka algorithm kūpono
ʻO ke koho o ka algorithm pololei e pili ana i ka pilikia e hoʻoholo ʻia, ka ʻano o ka ʻikepili y el nivel de pololei noi ʻia. No ka laʻana, kūpono nā papa helu laina e like me SVM no ka ʻikepili maʻalahi, ʻoiai ʻoi aku ka maikaʻi o nā neural network no nā pilikia paʻakikī e like me ka ʻōlelo a i ʻole ka ʻike kiʻi.
Eia kekahi, he mea koʻikoʻi ka loiloi a hoʻoponopono i nā ʻāpana o nā algorithm e hoʻokō i ka hana maikaʻi loa. E hoʻohana i nā ʻenehana e like me validación cruzada a me nā metric like pololei, hiki i ka hoʻihoʻi hou a me ka F1-helu ke kōkua i ka hoʻoholo ʻana i ka pono o ke kumu hoʻohālike.
He hana koʻikoʻi ka algorithm classification i ka hoʻoponopono ʻana i nā pilikia e koi ana i nā hoʻoholo hoʻoholo i ka ʻikepili, kākoʻo i nā mea āpau mai nā hoʻolaha kūʻai aku i ka noiʻi olakino, mau me ka pahuhopu o ka hoʻololi ʻana i ka ʻikepili i ʻike pono a hiki ke hana.
He kanaka ʻenehana wau i hoʻololi i kāna mau makemake "geek" i ʻoihana. Ua hoʻohana au ma mua o 10 mau makahiki o koʻu ola me ka hoʻohana ʻana i ka ʻenehana ʻokiʻoki a me ka hoʻomaʻamaʻa ʻana i nā ʻano papahana āpau ma muli o ka ʻike maʻemaʻe. I kēia manawa ua loea wau i ka ʻenehana kamepiula a me nā pāʻani wikiō. ʻO kēia no ka mea ʻoi aku ma mua o 5 mau makahiki aʻu i kākau ai no nā pūnaewele like ʻole e pili ana i ka ʻenehana a me nā pāʻani wikiō, e hana ana i nā ʻatikala e ʻimi nei e hāʻawi iā ʻoe i ka ʻike āu e pono ai ma kahi ʻōlelo i hoʻomaopopo ʻia e nā mea a pau.
Inā he mau nīnau kāu, pili koʻu ʻike mai nā mea a pau e pili ana i ka ʻōnaehana hana Windows a me Android no nā kelepona paʻalima. A ʻo kaʻu hoʻohiki ʻana iā ʻoe, makemake mau wau e hoʻolilo i mau minuke a kōkua iā ʻoe e hoʻoholo i nā nīnau āu e loaʻa ai ma kēia ao pūnaewele.