各位老铁们好，相信很多人对人工智能学习模型算法都不是特别的了解，因此呢，今天就来为大家分享下关于人工智能学习模型算法以及人工智能模型与算法的问题知识，还望可以帮助大家，解决大家的一些困惑，下面一起来看看吧！
本文目录
人工智能开发机器学习的常用算法
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鏀寔鍚戦噺鏈烘槸浠€涔?
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閭ｄ箞鏄粈涔堣瀹冨姝や紵澶у憿?
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閭ｄ箞鏍告妧宸ф槸浠€涔?
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机器学习有哪些算法
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Python涓殑鏁版嵁绉戝搴撳疄鐜癗aïveBayes-Sci-Kit瀛︿範
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R涓殑鏁版嵁绉戝搴撳疄鐜扮嚎鎬у洖褰?-缁熻
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Adaboost
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鏈寸礌璐濆彾鏂?/strong>
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K杩戦偦
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SVM
浣跨敤閾伴摼鎹熷け鍑芥暟璁＄畻缁忛獙椋庨櫓骞跺湪姹傝В绯荤粺涓姞鍏ヤ簡姝ｅ垯鍖栭」浠ヤ紭鍖栫粨鏋勯闄╋紝鏄竴涓叿鏈夌█鐤忔€у拰绋冲仴鎬х殑鍒嗙被鍣ㄣ€?/p>
绁炵粡缃戠粶
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人工智能算法简介
浜哄伐鏅鸿兘鐨勪笁澶у熀鐭斥€旂畻娉曘€佹暟鎹拰璁＄畻鑳藉姏锛岀畻娉曚綔涓哄叾涓箣涓€锛屾槸闈炲父閲嶈鐨勶紝閭ｄ箞浜哄伐鏅鸿兘閮戒細娑夊強鍝簺绠楁硶鍛紵涓嶅悓绠楁硶閫傜敤浜庡摢浜涘満鏅憿锛?br/>
涓€銆佹寜鐓фā鍨嬭缁冩柟寮忎笉鍚屽彲浠ュ垎涓虹洃鐫ｅ涔狅紙SupervisedLearning锛夛紝鏃犵洃鐫ｅ涔狅紙UnsupervisedLearning锛夈€佸崐鐩戠潱瀛︿範锛圫emi-supervisedLearning锛夊拰寮哄寲瀛︿範锛圧einforcementLearning锛夊洓澶х被銆?br/>
甯歌鐨勭洃鐫ｅ涔犵畻娉曞寘鍚互涓嬪嚑绫伙細
锛?锛変汉宸ョ缁忕綉缁滐紙ArtificialNeuralNetwork锛夌被锛氬弽鍚戜紶鎾紙Backpropagation锛夈€佹尝灏斿吂鏇兼満锛圔oltzmannMachine锛夈€佸嵎绉缁忕綉缁滐紙ConvolutionalNeuralNetwork锛夈€丠opfield缃戠粶锛坔opfieldNetwork锛夈€佸灞傛劅鐭ュ櫒锛圡ultilyerPerceptron锛夈€佸緞鍚戝熀鍑芥暟缃戠粶锛圧adialBasisFunctionNetwork锛孯BFN锛夈€佸彈闄愭尝灏斿吂鏇兼満锛圧estrictedBoltzmannMachine锛夈€佸洖褰掔缁忕綉缁滐紙RecurrentNeuralNetwork锛孯NN锛夈€佽嚜缁勭粐鏄犲皠锛圫elf-organizingMap锛孲OM锛夈€佸皷宄扮缁忕綉缁滐紙SpikingNeuralNetwork锛夌瓑銆?br/>锛?锛夎礉鍙舵柉绫伙紙Bayesin锛夛細鏈寸礌璐濆彾鏂紙NaiveBayes锛夈€侀珮鏂礉鍙舵柉锛圙aussianNaiveBayes锛夈€佸椤规湸绱犺礉鍙舵柉锛圡ultinomialNaiveBayes锛夈€佸钩鍧?渚濊禆鎬ц瘎浼帮紙AveragedOne-DependenceEstimators锛孉ODE锛?br/>璐濆彾鏂俊蹇电綉缁滐紙BayesianBeliefNetwork锛孊BN锛夈€佽礉鍙舵柉缃戠粶锛圔ayesianNetwork锛孊N锛夌瓑銆?br/>锛?锛夊喅绛栨爲锛圖ecisionTree锛夌被锛氬垎绫诲拰鍥炲綊鏍戯紙ClassificationandRegressionTree锛孋ART锛夈€佽凯浠ichotomiser3锛圛terativeDichotomiser3锛?ID3锛?C4.5绠楁硶锛圕4.5Algorithm锛夈€丆5.0绠楁硶锛圕5.0Algorithm锛夈€佸崱鏂硅嚜鍔ㄤ氦浜掓娴嬶紙Chi-squaredAutomaticInteractionDetection锛孋HAID锛夈€佸喅绛栨畫绔紙DecisionStump锛夈€両D3绠楁硶锛圛D3Algorithm锛夈€侀殢鏈烘．鏋楋紙RandomForest锛夈€丼LIQ锛圫upervisedLearninginQuest锛夌瓑銆?br/>锛?锛夌嚎鎬у垎绫诲櫒锛圠inearClassifier锛夌被锛欶isher鐨勭嚎鎬у垽鍒紙Fisher鈥檚LinearDiscriminant锛?br/>绾挎€у洖褰掞紙LinearRegression锛夈€侀€昏緫鍥炲綊锛圠ogisticRegression锛夈€佸椤归€昏緫鍥炲綊锛圡ultionmialLogisticRegression锛夈€佹湸绱犺礉鍙舵柉鍒嗙被鍣紙NaiveBayesClassifier锛夈€佹劅鐭ワ紙Perception锛夈€佹敮鎸佸悜閲忔満锛圫upportVectorMachine锛夌瓑銆?br/>
甯歌鐨勬棤鐩戠潱瀛︿範绫荤畻娉曞寘鎷細
锛?锛?浜哄伐绁炵粡缃戠粶锛圓rtificialNeuralNetwork锛夌被锛氱敓鎴愬鎶楃綉缁滐紙GenerativeAdversarialNetworks锛孏AN锛夛紝鍓嶉绁炵粡缃戠粶锛團eedforwardNeuralNetwork锛夈€侀€昏緫瀛︿範鏈猴紙LogicLearningMachine锛夈€佽嚜缁勭粐鏄犲皠锛圫elf-organizingMap锛夌瓑銆?br/>锛?锛?鍏宠仈瑙勫垯瀛︿範锛圓ssociationRuleLearning锛夌被锛氬厛楠岀畻娉曪紙AprioriAlgorithm锛夈€丒clat绠楁硶锛圗clatAlgorithm锛夈€丗P-Growth绠楁硶绛夈€?br/>锛?锛夊垎灞傝仛绫荤畻娉曪紙HierarchicalClustering锛夛細鍗曡繛閿佽仛绫伙紙Single-linkageClustering锛夛紝姒傚康鑱氱被锛圕onceptualClustering锛夌瓑銆?br/>锛?锛夎仛绫诲垎鏋愶紙Clusteranalysis锛夛細BIRCH绠楁硶銆丏BSCAN绠楁硶锛屾湡鏈涙渶澶у寲锛圗xpectation-maximization锛孍M锛夈€佹ā绯婅仛绫伙紙FuzzyClustering锛夈€並-means绠楁硶銆並鍧囧€艰仛绫伙紙K-meansClustering锛夈€並-medians鑱氱被銆佸潎鍊兼紓绉荤畻娉曪紙Mean-shift锛夈€丱PTICS绠楁硶绛夈€?br/>锛?锛夊紓甯告娴嬶紙Anomalydetection锛夌被锛欿鏈€閭昏繎锛圞-nearestNeighbor锛孠NN锛夌畻娉曪紝灞€閮ㄥ紓甯稿洜瀛愮畻娉曪紙LocalOutlierFactor锛孡OF锛夌瓑銆?br/>
甯歌鐨勫崐鐩戠潱瀛︿範绫荤畻娉曞寘鍚細鐢熸垚妯″瀷锛圙enerativeModels锛夈€佷綆瀵嗗害鍒嗙锛圠ow-densitySeparation锛夈€佸熀浜庡浘褰㈢殑鏂规硶锛圙raph-basedMethods锛夈€佽仈鍚堣缁冿紙Co-training锛夌瓑銆?br/>
甯歌鐨勫己鍖栧涔犵被绠楁硶鍖呭惈锛歈瀛︿範锛圦-learning锛夈€佺姸鎬?琛屽姩-濂栧姳-鐘舵€?琛屽姩锛圫tate-Action-Reward-State-Action锛孲ARSA锛夈€丏QN锛圖eepQNetwork锛夈€佺瓥鐣ユ搴︾畻娉曪紙PolicyGradients锛夈€佸熀浜庢ā鍨嬪己鍖栧涔狅紙ModelBasedRL锛夈€佹椂搴忓樊鍒嗗涔狅紙TemporalDifferentLearning锛夌瓑銆?br/>
甯歌鐨勬繁搴﹀涔犵被绠楁硶鍖呭惈锛氭繁搴︿俊蹇电綉缁滐紙DeepBeliefMachines锛夈€佹繁搴﹀嵎绉缁忕綉缁滐紙DeepConvolutionalNeuralNetworks锛夈€佹繁搴﹂€掑綊绁炵粡缃戠粶锛圖eepRecurrentNeuralNetwork锛夈€佸垎灞傛椂闂磋蹇嗭紙HierarchicalTemporalMemory锛孒TM锛夈€佹繁搴︽尝灏斿吂鏇兼満锛圖eepBoltzmannMachine锛孌BM锛夈€佹爤寮忚嚜鍔ㄧ紪鐮佸櫒锛圫tackedAutoencoder锛夈€佺敓鎴愬鎶楃綉缁滐紙GenerativeAdversarialNetworks锛夌瓑銆?br/>
浜屻€佹寜鐓цВ鍐充换鍔＄殑涓嶅悓鏉ュ垎绫伙紝绮楃暐鍙互鍒嗕负浜屽垎绫荤畻娉曪紙Two-classClassification锛夈€佸鍒嗙被绠楁硶锛圡ulti-classClassification锛夈€佸洖褰掔畻娉曪紙Regression锛夈€佽仛绫荤畻娉曪紙Clustering锛夊拰寮傚父妫€娴嬶紙AnomalyDetection锛変簲绉嶃€?br/>1.浜屽垎绫伙紙Two-classClassification锛?br/>锛?锛変簩鍒嗙被鏀寔鍚戦噺鏈猴紙Two-classSVM锛夛細閫傜敤浜庢暟鎹壒寰佽緝澶氥€佺嚎鎬фā鍨嬬殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被骞冲潎鎰熺煡鍣紙Two-classAveragePerceptron锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺嚎鎬фā鍨嬬殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被閫昏緫鍥炲綊锛圱wo-classLogisticRegression锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺嚎鎬фā鍨嬬殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被璐濆彾鏂偣鏈猴紙Two-classBayesPointMachine锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺嚎鎬фā鍨嬬殑鍦烘櫙銆傦紙5锛変簩鍒嗙被鍐崇瓥妫灄锛圱wo-classDecisionForest锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺簿鍑嗙殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被鎻愬崌鍐崇瓥鏍戯紙Two-classBoostedDecisionTree锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺簿鍑嗗害楂樸€佸唴瀛樺崰鐢ㄩ噺澶х殑鍦烘櫙
锛?锛変簩鍒嗙被鍐崇瓥涓涙灄锛圱wo-classDecisionJungle锛夛細閫傜敤浜庤缁冩椂闂寸煭銆佺簿纭害楂樸€佸唴瀛樺崰鐢ㄩ噺灏忕殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被灞€閮ㄦ繁搴︽敮鎸佸悜閲忔満锛圱wo-classLocallyDeepSVM锛夛細閫傜敤浜庢暟鎹壒寰佽緝澶氱殑鍦烘櫙銆?br/>锛?锛変簩鍒嗙被绁炵粡缃戠粶锛圱wo-classNeuralNetwork锛夛細閫傜敤浜庣簿鍑嗗害楂樸€佽缁冩椂闂磋緝闀跨殑鍦烘櫙銆?br/>
瑙ｅ喅澶氬垎绫婚棶棰橀€氬父閫傜敤涓夌瑙ｅ喅鏂规锛氱涓€绉嶏紝浠庢暟鎹泦鍜岄€傜敤鏂规硶鍏ユ墜锛屽埄鐢ㄤ簩鍒嗙被鍣ㄨВ鍐冲鍒嗙被闂锛涚浜岀锛岀洿鎺ヤ娇鐢ㄥ叿澶囧鍒嗙被鑳藉姏鐨勫鍒嗙被鍣紱绗笁绉嶏紝灏嗕簩鍒嗙被鍣ㄦ敼杩涙垚涓哄鍒嗙被鍣ㄤ粖鍎胯В鍐冲鍒嗙被闂銆?br/>甯哥敤鐨勭畻娉曪細
锛?锛夊鍒嗙被閫昏緫鍥炲綊锛圡ulticlassLogisticRegression锛夛細閫傜敤璁粌鏃堕棿鐭€佺嚎鎬фā鍨嬬殑鍦烘櫙銆?br/>锛?锛夊鍒嗙被绁炵粡缃戠粶锛圡ulticlassNeuralNetwork锛夛細閫傜敤浜庣簿鍑嗗害楂樸€佽缁冩椂闂磋緝闀跨殑鍦烘櫙銆?br/>锛?锛夊鍒嗙被鍐崇瓥妫灄锛圡ulticlassDecisionForest锛夛細閫傜敤浜庣簿鍑嗗害楂橈紝璁粌鏃堕棿鐭殑鍦烘櫙銆?br/>锛?锛夊鍒嗙被鍐崇瓥涓涙灄锛圡ulticlassDecisionJungle锛夛細閫傜敤浜庣簿鍑嗗害楂橈紝鍐呭瓨鍗犵敤杈冨皬鐨勫満鏅€?br/>锛?锛夆€滀竴瀵瑰鈥濆鍒嗙被锛圤ne-vs-allMulticlass锛夛細鍙栧喅浜庝簩鍒嗙被鍣ㄦ晥鏋溿€?br/>
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鍘熸枃閾炬帴锛?https://blog.csdn.net/nfzhlk/article/details/82725769
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