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鐩寸嚎鏂圭▼y=kx+b鏀逛负浜屾鏇茬嚎鏂圭▼y=ax^2+bx+c鏃讹紝鍙傛暟(Parameter)鐢?涓?鍒嗗埆鏄痥銆乥)鍙樹负3涓?鍒嗗埆鏄痑銆乥銆乧)锛?/span>鐗瑰緛(Feature)鐢?涓?x)鍙樹负2涓?x^2鍜寈)銆備笁娆℃洸绾垮拰澶嶆潅鐨勫椤瑰紡鍥炲綊浼氬鍔犳洿澶氱殑鍙傛暟鍜岀壒寰併€?/span>
鍓嶉潰璁茬殑鏄€荤粨涓€涓叉暟瀛楃殑瑙勫緥锛岀幇瀹炵敓娲讳腑鎴戜滑寰€寰€瑕佹牴鎹涓壒寰?澶氫覆鏁板瓧)鏉ュ垎鏋愪竴浠朵簨鎯咃紝姣忎釜鍘熷鐗瑰緛鎴戜滑閮界湅浣滄槸涓€涓?/span>缁村害(Dimension)銆備緥濡備竴涓鐢熺殑瀛︿範鎴愮哗濂藉潖瑕佹牴鎹鏂囥€佹暟瀛︺€佽嫳璇瓑澶氶棬璇剧▼鐨勫垎鏁版潵缁煎悎鍒ゆ柇锛岃繖閲屾瘡闂ㄨ绋嬮兘鏄竴涓淮搴︺€傚綋浣跨敤浜屾鏇茬嚎鍜屽鍙橀噺(澶氱淮)鎷熷悎鐨勬儏鍐典笅锛岀壒寰佺殑鏁伴噺浼氬墽澧烇紝鐗瑰緛鏁?缁村害^2/2 杩欎釜鍏紡鍙互澶ф璁＄畻鍑虹壒寰佸鍔犵殑鎯呭喌锛屼緥濡備竴涓?00缁寸殑鏁版嵁锛屼簩娆″椤瑰紡鎷熷悎鍚庯紝鐗瑰緛浼氬鍔犲埌100*100/2=5000涓€?/span>
涓嬮潰鏄竴寮?0*50鍍忕礌鐨勭伆搴﹀浘鐗囷紝濡傛灉鐢ㄤ簩娆″椤瑰紡鎷熷悎鐨勮瘽锛屽畠鏈夊灏戜釜鐗瑰緛鍛紵鈥斺€斿ぇ绾︽湁3鐧句竾锛?/span>
瀹冪殑缁村害鏄?0*50=2500锛岀壒寰佹暟=2500*2500/2=3,125,000銆傚鏋滄槸褰╄壊鍥剧墖锛岀淮搴︿細澧炲姞鍒板師鏉ョ殑3鍊嶏紝閭ｄ箞鐗瑰緛鏁板皢澧炲姞鍒版帴杩?鍗冧竾浜嗭紒
杩欎箞灏忕殑涓€寮犲浘鐗囷紝灏辨湁杩欎箞宸ㄥぇ鐨勭壒寰侀噺锛屽彲浠ユ兂鍍忎竴涓嬫垜浠殑鏁扮爜鐩告満鎷嶄笅鏉ョ殑鐓х墖浼氭湁澶氬ぇ鐨勭壒寰侀噺锛佽€屾垜浠鍋氱殑鏄粠鍗佷竾涔冭嚦浜夸竾寮犺繖鏍风殑鍥剧墖涓壘瑙勫緥锛岃繖鍙兘鍚楋紵
寰堟樉鐒讹紝鍓嶉潰鐨勯偅浜涘洖褰掓柟娉曞凡缁忎笉澶熺敤浜嗭紝鎴戜滑鎬ラ渶鎵惧埌涓€绉嶆暟瀛︽ā鍨嬶紝鑳藉鍦ㄦ鍩虹涓婁笉鏂噺灏戠壒寰侊紝闄嶄綆缁村害銆?/span>
浜庢槸锛屸€?/span>浜哄伐绁炵粡缃戠粶(ANN, Artificial Neural Network)鈥濆氨鍦ㄨ繖鏍疯嫑鍒荤殑鏉′欢涓嬬矇澧ㄧ櫥鍦轰簡锛岀缁忕瀛︾殑鐮旂┒鎴愭灉涓烘満鍣ㄥ涔犻鍩熷紑杈熶簡骞块様鐨勯亾璺€?/span>
鏈変竴绉嶅亣璇达細鈥滄櫤鑳芥潵婧愪簬鍗曚竴鐨勭畻娉?One Learning Algorithm)鈥濄€傚鏋滆繖涓€鍋囪鎴愮珛锛岄偅涔堝埄鐢ㄥ崟涓€鐨勭畻娉?绁炵粡缃戠粶)澶勭悊涓栫晫涓婂崈鍙樹竾鍖栫殑闂灏辨垚涓哄彲鑳姐€傛垜浠笉蹇呭涓囦簨涓囩墿杩涜缂栫▼锛屽彧闇€閲囩敤浠ヤ笉鍙樺簲涓囧彉鐨勭瓥鐣ュ嵆鍙€傛湁瓒婃潵瓒婂鐨勮瘉鎹瘉鏄庤繖绉嶅亣璇达紝渚嬪浜虹被澶ц剳鍙戣偛鍒濇湡锛屾瘡涓€閮ㄥ垎鐨勮亴璐ｅ垎宸ユ槸涓嶇‘瀹氱殑锛屼篃灏辨槸璇达紝浜鸿剳涓礋璐ｅ鐞嗗０闊崇殑閮ㄥ垎鍏跺疄涔熷彲浠ュ鐞嗚瑙夊奖鍍忋€?br>
绁炵粡鍏?Neuron)锛屾垨鑰呰涓€涓剳缁嗚優鐨勭敓鐞嗙粨鏋勶細
涓嬮潰鏄崟涓缁忓厓鐨勬暟瀛︽ā鍨嬶紝鍙互鐪嬪嚭瀹冩槸鐢熺悊缁撴瀯鐨勭畝鍖栫増锛屾ā浠跨殑杩樻尯鍍忥細
瑙ｉ噴涓€涓嬶細+1浠ｈ〃鍋忕Щ鍊?鍋忕疆椤? Bias Units)锛沊1,X2,X2浠ｈ〃鍒濆鐗瑰緛锛泈0,w1,w2,w3浠ｈ〃鏉冮噸(Weight)锛屽嵆鍙傛暟锛屾槸鐗瑰緛鐨勭缉鏀惧€嶆暟锛涚壒寰佺粡杩囩缉鏀惧拰鍋忕Щ鍚庡叏閮ㄧ疮鍔犺捣鏉ワ紝姝ゅ悗杩樿缁忚繃涓€娆℃縺娲昏繍绠楃劧鍚庡啀杈撳嚭銆傛縺娲诲嚱鏁版湁寰堝绉嶏紝鍚庨潰灏嗕細璇︾粏璇存槑銆?br>
涓句緥璇存槑锛?br>
X1*w1+X2*w2+...+Xn*wn杩欑璁＄畻鏂规硶绉颁负鍔犳潈姹傚拰(Weighted Sum)娉曪紝姝ゆ柟娉曞湪绾挎€т唬鏁伴噷鏋佷负甯哥敤銆傚姞鏉冩眰鍜岀殑鏍囧噯鏁板绗﹀彿鏄紝
杩欎釜鏁板妯″瀷鏈変粈涔堟剰涔夊憿锛熶笅闈㈡垜瀵圭収鍓嶉潰閭ｄ釜 y=kx+b 鐩寸嚎鎷熷悎鐨勪緥瀛愭潵璇存槑涓€涓嬨€?br>
杩欐椂鎴戜滑鎶婃縺娲诲嚱鏁版敼涓?span>Purelin(45搴︾洿绾?锛孭urelin灏辨槸y=x锛屼唬琛ㄤ繚鎸佸師鏉ョ殑鍊间笉鍙樸€?br>杩欐牱杈撳嚭鍊煎氨鎴愪簡 Y鐩寸嚎鐐?= b + X鐩寸嚎鐐?k锛屽嵆y=kx+b銆傜湅鍒颁簡鍚э紝鍙槸鎹簡涓┈鐢茶€屽凡锛岃繕璁ょ殑鍑烘潵鍚楋紵涓嬩竴姝ワ紝瀵逛簬姣忎釜鐐归兘杩涜杩欑杩愮畻锛屽埄鐢╕鐩寸嚎鐐瑰拰Y鏍锋湰鐐硅绠楄宸紝鎶婅宸疮鍔犺捣鏉ワ紝涓嶆柇鍦版洿鏂癰銆乲鐨勫€硷紝鐢辨涓嶆柇鍦扮Щ鍔ㄥ拰鏃嬭浆鐩寸嚎锛岀洿鍒拌宸彉寰楀緢灏忔椂鍋滀綇(鏀舵暃)銆傝繖涓繃绋嬪畬鍏ㄥ氨鏄墠闈㈣杩囩殑姊害涓嬮檷鐨勭嚎鎬у洖褰掋€?br>
涓€鑸洿绾挎嫙鍚堢殑绮剧‘搴﹁姣旀洸绾垮樊寰堝锛岄偅涔堜娇鐢ㄧ缁忕綉缁滄垜浠皢濡備綍浣跨敤鏇茬嚎鎷熷悎锛熺瓟妗堟槸浣跨敤闈炵嚎鎬х殑婵€娲诲嚱鏁板嵆鍙紝鏈€甯歌鐨勬縺娲诲嚱鏁版槸Sigmoid(S褰㈡洸绾?锛孲igmoid鏈夋椂涔熺О涓?span>閫昏緫鍥炲綊(Logistic Regression)锛岀畝绉?span>logsig銆俵ogsig鏇茬嚎鐨勫叕寮忓涓嬶細
涓嬪浘鏄嚑绉嶆瘮杈冨父瑙佺殑缃戠粶褰㈠紡锛?br>
濡傛灉鐢╰ansig浣滄縺娲诲嚱鏁帮紝閭ｄ箞锛歵ansig瀵兼暟 = 1 - tansig^2
娈嬪樊鍏ㄩ儴璁＄畻濂藉悗锛屽氨鍙互鏇存柊鏉冮噸浜嗭細
杈撳叆灞傦細鏉冮噸澧炲姞 = 杈撳叆鍊?* 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?/p>
闅愯棌灞傦細鏉冮噸澧炲姞 = 褰撳墠鑺傜偣鐨凷igmoid * 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?br>鍋忕Щ鍊肩殑鏉冮噸澧炲姞 = 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?br>瀛︿範鐜囧墠闈粙缁嶈繃锛屽涔犵巼鏄竴涓鍏堣缃ソ鐨勫弬鏁帮紝鐢ㄤ簬鎺у埗姣忔鏇存柊鐨勫箙搴︺€?br>
姝ゅ悗锛屽鍏ㄩ儴鏁版嵁閮藉弽澶嶈繘琛岃繖鏍风殑璁＄畻锛岀洿鍒拌緭鍑虹殑璇樊杈惧埌涓€涓緢灏忕殑鍊间负姝€?/p>
浠ヤ笂浠嬬粛鐨勬槸鐩墠鏈€甯歌鐨勭缁忕綉缁滅被鍨嬶紝绉颁负鍓嶉绁炵粡缃戠粶(FeedForward Neural Network)锛岀敱浜庡畠涓€鑸槸瑕佸悜鍚庝紶閫掕宸殑锛屾墍浠ヤ篃鍙?span>BP绁炵粡缃戠粶(Back Propagation Neural Network)銆?br>
BP绁炵粡缃戠粶鐨勭壒鐐瑰拰灞€闄愶細
- BP绁炵粡缃戠粶鍙互鐢ㄤ綔鍒嗙被銆佽仛绫汇€侀娴嬬瓑銆傞渶瑕佹湁涓€瀹氶噺鐨勫巻鍙叉暟鎹紝閫氳繃鍘嗗彶鏁版嵁鐨勮缁冿紝缃戠粶鍙互瀛︿範鍒版暟鎹腑闅愬惈鐨勭煡璇嗐€傚湪浣犵殑闂涓紝棣栧厛瑕佹壘鍒版煇浜涢棶棰樼殑涓€浜涚壒寰侊紝浠ュ強瀵瑰簲鐨勮瘎浠锋暟鎹紝鐢ㄨ繖浜涙暟鎹潵璁粌绁炵粡缃戠粶銆?br>- BP绁炵粡缃戠粶涓昏鏄湪瀹炶返鐨勫熀纭€涓婇€愭瀹屽杽璧锋潵鐨勭郴缁燂紝骞朵笉瀹屽叏鏄缓绔嬪湪浠跨敓瀛︿笂鐨勩€備粠杩欎釜瑙掑害璁诧紝瀹炵敤鎬?> 鐢熺悊鐩镐技鎬с€?br>- BP绁炵粡缃戠粶涓殑鏌愪簺绠楁硶锛屼緥濡傚浣曢€夋嫨鍒濆鍊笺€佸浣曠‘瀹氶殣钘忓眰鐨勮妭鐐逛釜鏁般€佷娇鐢ㄤ綍绉嶆縺娲诲嚱鏁扮瓑闂锛屽苟娌℃湁纭嚳鐨勭悊璁轰緷鎹紝鍙湁涓€浜涙牴鎹疄璺电粡楠屾€荤粨鍑虹殑鏈夋晥鏂规硶鎴栫粡楠屽叕寮忋€?br>- BP绁炵粡缃戠粶铏界劧鏄竴绉嶉潪甯告湁鏁堢殑璁＄畻鏂规硶锛屼絾瀹冧篃浠ヨ绠楄秴澶嶆潅銆佽绠楅€熷害瓒呮參銆佸鏄撻櫡鍏ュ眬閮ㄦ渶浼樿В绛夊椤瑰急鐐硅憲绉帮紝鍥犳浜轰滑鎻愬嚭浜嗗ぇ閲忔湁鏁堢殑鏀硅繘鏂规锛屼竴浜涙柊鐨勭缁忕綉缁滃舰寮忎篃灞傚嚭涓嶇┓銆?/p>
杩欓噷浠嬬粛鐨勬槸璁＄畻瀹屼竴鏉¤褰曪紝灏遍┈涓婃洿鏂版潈閲嶏紝浠ュ悗姣忚绠楀畬涓€鏉￠兘鍗虫椂鏇存柊鏉冮噸銆傚疄闄呬笂鎵归噺鏇存柊鐨勬晥鏋滀細鏇村ソ锛屾柟娉曟槸鍦ㄤ笉鏇存柊鏉冮噸鐨勬儏鍐典笅锛屾妸璁板綍闆嗙殑姣忔潯璁板綍閮界畻杩囦竴閬嶏紝鎶婅鏇存柊鐨勫鍊煎叏閮ㄧ疮鍔犺捣鏉ユ眰骞冲潎鍊硷紝鐒跺悗鍒╃敤杩欎釜骞冲潎鍊兼潵鏇存柊涓€娆℃潈閲嶏紝鐒跺悗鍒╃敤鏇存柊鍚庣殑鏉冮噸杩涜涓嬩竴杞殑璁＄畻锛岃繖绉嶆柟娉曞彨鎵归噺姊害涓嬮檷(Batch Gradient Descent)銆?/p>
Andrew Ng鐨勩€婃満鍣ㄥ涔犮€嬪叕寮€璇? https://class.coursera.org/ml
Coursera鍏紑璇剧瑪璁颁腑鏂囩増锛堢缁忕綉缁滅殑琛ㄧず锛? http://52opencourse.com/139/coursera鍏紑璇剧瑪璁?鏂潶绂忓ぇ瀛︽満鍣ㄥ涔犵鍏-绁炵粡缃戠粶鐨勮〃绀?neural-networks-representation
Coursera鍏紑璇捐棰戯紙绁炵粡缃戠粶鐨勫涔狅級: http://52opencourse.com/289/coursera鍏紑璇捐棰?鏂潶绂忓ぇ瀛︽満鍣ㄥ涔犵涔濊-绁炵粡缃戠粶鐨勫涔?neural-networks-learning
鏂潶绂忔繁搴﹀涔犱腑鏂囩増锛?http://deeplearning.stanford.edu/wiki/index.php/UFLDL鏁欑▼
闃呰杩囨湰鏂囩殑浜鸿繕鐪嬩簡浠ヤ笅锛?/strong>
涓嶆柇鏇存柊璧勬簮
娣卞害瀛︿範銆佹満鍣ㄥ涔犮€佹暟鎹垎鏋愩€乸ython
以上是关于鍏ラ棬娣卞害瀛︿範锛岀悊瑙ｇ缁忕綉缁溿€佸弽鍚戜紶鎾畻娉曟槸绗竴鍏?/h1>
Posted 鏈哄櫒瀛︿範AI绠楁硶宸ョ▼
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篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了鍏ラ棬娣卞害瀛︿範锛岀悊瑙ｇ缁忕綉缁溿€佸弽鍚戜紶鎾畻娉曟槸绗竴鍏?/h1>
鍚慉I杞瀷鐨勭▼搴忓憳閮藉叧娉ㄤ簡杩欎釜鍙?/span>馃憞馃憞馃憞
娣卞害瀛︿範瀛︿範7姝ラ
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鍓嶉潰璁茬殑鏄€荤粨涓€涓叉暟瀛楃殑瑙勫緥锛岀幇瀹炵敓娲讳腑鎴戜滑寰€寰€瑕佹牴鎹涓壒寰?澶氫覆鏁板瓧)鏉ュ垎鏋愪竴浠朵簨鎯咃紝姣忎釜鍘熷鐗瑰緛鎴戜滑閮界湅浣滄槸涓€涓?/span>缁村害(Dimension)銆備緥濡備竴涓鐢熺殑瀛︿範鎴愮哗濂藉潖瑕佹牴鎹鏂囥€佹暟瀛︺€佽嫳璇瓑澶氶棬璇剧▼鐨勫垎鏁版潵缁煎悎鍒ゆ柇锛岃繖閲屾瘡闂ㄨ绋嬮兘鏄竴涓淮搴︺€傚綋浣跨敤浜屾鏇茬嚎鍜屽鍙橀噺(澶氱淮)鎷熷悎鐨勬儏鍐典笅锛岀壒寰佺殑鏁伴噺浼氬墽澧烇紝鐗瑰緛鏁?缁村害^2/2 杩欎釜鍏紡鍙互澶ф璁＄畻鍑虹壒寰佸鍔犵殑鎯呭喌锛屼緥濡備竴涓?00缁寸殑鏁版嵁锛屼簩娆″椤瑰紡鎷熷悎鍚庯紝鐗瑰緛浼氬鍔犲埌100*100/2=5000涓€?/span>
涓嬮潰鏄竴寮?0*50鍍忕礌鐨勭伆搴﹀浘鐗囷紝濡傛灉鐢ㄤ簩娆″椤瑰紡鎷熷悎鐨勮瘽锛屽畠鏈夊灏戜釜鐗瑰緛鍛紵鈥斺€斿ぇ绾︽湁3鐧句竾锛?/span>
瀹冪殑缁村害鏄?0*50=2500锛岀壒寰佹暟=2500*2500/2=3,125,000銆傚鏋滄槸褰╄壊鍥剧墖锛岀淮搴︿細澧炲姞鍒板師鏉ョ殑3鍊嶏紝閭ｄ箞鐗瑰緛鏁板皢澧炲姞鍒版帴杩?鍗冧竾浜嗭紒
杩欎箞灏忕殑涓€寮犲浘鐗囷紝灏辨湁杩欎箞宸ㄥぇ鐨勭壒寰侀噺锛屽彲浠ユ兂鍍忎竴涓嬫垜浠殑鏁扮爜鐩告満鎷嶄笅鏉ョ殑鐓х墖浼氭湁澶氬ぇ鐨勭壒寰侀噺锛佽€屾垜浠鍋氱殑鏄粠鍗佷竾涔冭嚦浜夸竾寮犺繖鏍风殑鍥剧墖涓壘瑙勫緥锛岃繖鍙兘鍚楋紵
寰堟樉鐒讹紝鍓嶉潰鐨勯偅浜涘洖褰掓柟娉曞凡缁忎笉澶熺敤浜嗭紝鎴戜滑鎬ラ渶鎵惧埌涓€绉嶆暟瀛︽ā鍨嬶紝鑳藉鍦ㄦ鍩虹涓婁笉鏂噺灏戠壒寰侊紝闄嶄綆缁村害銆?/span>
浜庢槸锛屸€?/span>浜哄伐绁炵粡缃戠粶(ANN, Artificial Neural Network)鈥濆氨鍦ㄨ繖鏍疯嫑鍒荤殑鏉′欢涓嬬矇澧ㄧ櫥鍦轰簡锛岀缁忕瀛︾殑鐮旂┒鎴愭灉涓烘満鍣ㄥ涔犻鍩熷紑杈熶簡骞块様鐨勯亾璺€?/span>
鏈変竴绉嶅亣璇达細鈥滄櫤鑳芥潵婧愪簬鍗曚竴鐨勭畻娉?One Learning Algorithm)鈥濄€傚鏋滆繖涓€鍋囪鎴愮珛锛岄偅涔堝埄鐢ㄥ崟涓€鐨勭畻娉?绁炵粡缃戠粶)澶勭悊涓栫晫涓婂崈鍙樹竾鍖栫殑闂灏辨垚涓哄彲鑳姐€傛垜浠笉蹇呭涓囦簨涓囩墿杩涜缂栫▼锛屽彧闇€閲囩敤浠ヤ笉鍙樺簲涓囧彉鐨勭瓥鐣ュ嵆鍙€傛湁瓒婃潵瓒婂鐨勮瘉鎹瘉鏄庤繖绉嶅亣璇达紝渚嬪浜虹被澶ц剳鍙戣偛鍒濇湡锛屾瘡涓€閮ㄥ垎鐨勮亴璐ｅ垎宸ユ槸涓嶇‘瀹氱殑锛屼篃灏辨槸璇达紝浜鸿剳涓礋璐ｅ鐞嗗０闊崇殑閮ㄥ垎鍏跺疄涔熷彲浠ュ鐞嗚瑙夊奖鍍忋€?br>
绁炵粡鍏?Neuron)锛屾垨鑰呰涓€涓剳缁嗚優鐨勭敓鐞嗙粨鏋勶細
涓嬮潰鏄崟涓缁忓厓鐨勬暟瀛︽ā鍨嬶紝鍙互鐪嬪嚭瀹冩槸鐢熺悊缁撴瀯鐨勭畝鍖栫増锛屾ā浠跨殑杩樻尯鍍忥細
瑙ｉ噴涓€涓嬶細+1浠ｈ〃鍋忕Щ鍊?鍋忕疆椤? Bias Units)锛沊1,X2,X2浠ｈ〃鍒濆鐗瑰緛锛泈0,w1,w2,w3浠ｈ〃鏉冮噸(Weight)锛屽嵆鍙傛暟锛屾槸鐗瑰緛鐨勭缉鏀惧€嶆暟锛涚壒寰佺粡杩囩缉鏀惧拰鍋忕Щ鍚庡叏閮ㄧ疮鍔犺捣鏉ワ紝姝ゅ悗杩樿缁忚繃涓€娆℃縺娲昏繍绠楃劧鍚庡啀杈撳嚭銆傛縺娲诲嚱鏁版湁寰堝绉嶏紝鍚庨潰灏嗕細璇︾粏璇存槑銆?br>
涓句緥璇存槑锛?br>
X1*w1+X2*w2+...+Xn*wn杩欑璁＄畻鏂规硶绉颁负鍔犳潈姹傚拰(Weighted Sum)娉曪紝姝ゆ柟娉曞湪绾挎€т唬鏁伴噷鏋佷负甯哥敤銆傚姞鏉冩眰鍜岀殑鏍囧噯鏁板绗﹀彿鏄紝
杩欎釜鏁板妯″瀷鏈変粈涔堟剰涔夊憿锛熶笅闈㈡垜瀵圭収鍓嶉潰閭ｄ釜 y=kx+b 鐩寸嚎鎷熷悎鐨勪緥瀛愭潵璇存槑涓€涓嬨€?br>
杩欐椂鎴戜滑鎶婃縺娲诲嚱鏁版敼涓?span>Purelin(45搴︾洿绾?锛孭urelin灏辨槸y=x锛屼唬琛ㄤ繚鎸佸師鏉ョ殑鍊间笉鍙樸€?br>杩欐牱杈撳嚭鍊煎氨鎴愪簡 Y鐩寸嚎鐐?= b + X鐩寸嚎鐐?k锛屽嵆y=kx+b銆傜湅鍒颁簡鍚э紝鍙槸鎹簡涓┈鐢茶€屽凡锛岃繕璁ょ殑鍑烘潵鍚楋紵涓嬩竴姝ワ紝瀵逛簬姣忎釜鐐归兘杩涜杩欑杩愮畻锛屽埄鐢╕鐩寸嚎鐐瑰拰Y鏍锋湰鐐硅绠楄宸紝鎶婅宸疮鍔犺捣鏉ワ紝涓嶆柇鍦版洿鏂癰銆乲鐨勫€硷紝鐢辨涓嶆柇鍦扮Щ鍔ㄥ拰鏃嬭浆鐩寸嚎锛岀洿鍒拌宸彉寰楀緢灏忔椂鍋滀綇(鏀舵暃)銆傝繖涓繃绋嬪畬鍏ㄥ氨鏄墠闈㈣杩囩殑姊害涓嬮檷鐨勭嚎鎬у洖褰掋€?br>
涓€鑸洿绾挎嫙鍚堢殑绮剧‘搴﹁姣旀洸绾垮樊寰堝锛岄偅涔堜娇鐢ㄧ缁忕綉缁滄垜浠皢濡備綍浣跨敤鏇茬嚎鎷熷悎锛熺瓟妗堟槸浣跨敤闈炵嚎鎬х殑婵€娲诲嚱鏁板嵆鍙紝鏈€甯歌鐨勬縺娲诲嚱鏁版槸Sigmoid(S褰㈡洸绾?锛孲igmoid鏈夋椂涔熺О涓?span>閫昏緫鍥炲綊(Logistic Regression)锛岀畝绉?span>logsig銆俵ogsig鏇茬嚎鐨勫叕寮忓涓嬶細
涓嬪浘鏄嚑绉嶆瘮杈冨父瑙佺殑缃戠粶褰㈠紡锛?br>
濡傛灉鐢╰ansig浣滄縺娲诲嚱鏁帮紝閭ｄ箞锛歵ansig瀵兼暟 = 1 - tansig^2
娈嬪樊鍏ㄩ儴璁＄畻濂藉悗锛屽氨鍙互鏇存柊鏉冮噸浜嗭細
杈撳叆灞傦細鏉冮噸澧炲姞 = 杈撳叆鍊?* 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?/p>
闅愯棌灞傦細鏉冮噸澧炲姞 = 褰撳墠鑺傜偣鐨凷igmoid * 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?br>鍋忕Щ鍊肩殑鏉冮噸澧炲姞 = 鍙冲眰瀵瑰簲鑺傜偣鐨勬畫宸?* 瀛︿範鐜?br>瀛︿範鐜囧墠闈粙缁嶈繃锛屽涔犵巼鏄竴涓鍏堣缃ソ鐨勫弬鏁帮紝鐢ㄤ簬鎺у埗姣忔鏇存柊鐨勫箙搴︺€?br>
姝ゅ悗锛屽鍏ㄩ儴鏁版嵁閮藉弽澶嶈繘琛岃繖鏍风殑璁＄畻锛岀洿鍒拌緭鍑虹殑璇樊杈惧埌涓€涓緢灏忕殑鍊间负姝€?/p>
浠ヤ笂浠嬬粛鐨勬槸鐩墠鏈€甯歌鐨勭缁忕綉缁滅被鍨嬶紝绉颁负鍓嶉绁炵粡缃戠粶(FeedForward Neural Network)锛岀敱浜庡畠涓€鑸槸瑕佸悜鍚庝紶閫掕宸殑锛屾墍浠ヤ篃鍙?span>BP绁炵粡缃戠粶(Back Propagation Neural Network)銆?br>
BP绁炵粡缃戠粶鐨勭壒鐐瑰拰灞€闄愶細
- BP绁炵粡缃戠粶鍙互鐢ㄤ綔鍒嗙被銆佽仛绫汇€侀娴嬬瓑銆傞渶瑕佹湁涓€瀹氶噺鐨勫巻鍙叉暟鎹紝閫氳繃鍘嗗彶鏁版嵁鐨勮缁冿紝缃戠粶鍙互瀛︿範鍒版暟鎹腑闅愬惈鐨勭煡璇嗐€傚湪浣犵殑闂涓紝棣栧厛瑕佹壘鍒版煇浜涢棶棰樼殑涓€浜涚壒寰侊紝浠ュ強瀵瑰簲鐨勮瘎浠锋暟鎹紝鐢ㄨ繖浜涙暟鎹潵璁粌绁炵粡缃戠粶銆?br>- BP绁炵粡缃戠粶涓昏鏄湪瀹炶返鐨勫熀纭€涓婇€愭瀹屽杽璧锋潵鐨勭郴缁燂紝骞朵笉瀹屽叏鏄缓绔嬪湪浠跨敓瀛︿笂鐨勩€備粠杩欎釜瑙掑害璁诧紝瀹炵敤鎬?> 鐢熺悊鐩镐技鎬с€?br>- BP绁炵粡缃戠粶涓殑鏌愪簺绠楁硶锛屼緥濡傚浣曢€夋嫨鍒濆鍊笺€佸浣曠‘瀹氶殣钘忓眰鐨勮妭鐐逛釜鏁般€佷娇鐢ㄤ綍绉嶆縺娲诲嚱鏁扮瓑闂锛屽苟娌℃湁纭嚳鐨勭悊璁轰緷鎹紝鍙湁涓€浜涙牴鎹疄璺电粡楠屾€荤粨鍑虹殑鏈夋晥鏂规硶鎴栫粡楠屽叕寮忋€?br>- BP绁炵粡缃戠粶铏界劧鏄竴绉嶉潪甯告湁鏁堢殑璁＄畻鏂规硶锛屼絾瀹冧篃浠ヨ绠楄秴澶嶆潅銆佽绠楅€熷害瓒呮參銆佸鏄撻櫡鍏ュ眬閮ㄦ渶浼樿В绛夊椤瑰急鐐硅憲绉帮紝鍥犳浜轰滑鎻愬嚭浜嗗ぇ閲忔湁鏁堢殑鏀硅繘鏂规锛屼竴浜涙柊鐨勭缁忕綉缁滃舰寮忎篃灞傚嚭涓嶇┓銆?/p>
杩欓噷浠嬬粛鐨勬槸璁＄畻瀹屼竴鏉¤褰曪紝灏遍┈涓婃洿鏂版潈閲嶏紝浠ュ悗姣忚绠楀畬涓€鏉￠兘鍗虫椂鏇存柊鏉冮噸銆傚疄闄呬笂鎵归噺鏇存柊鐨勬晥鏋滀細鏇村ソ锛屾柟娉曟槸鍦ㄤ笉鏇存柊鏉冮噸鐨勬儏鍐典笅锛屾妸璁板綍闆嗙殑姣忔潯璁板綍閮界畻杩囦竴閬嶏紝鎶婅鏇存柊鐨勫鍊煎叏閮ㄧ疮鍔犺捣鏉ユ眰骞冲潎鍊硷紝鐒跺悗鍒╃敤杩欎釜骞冲潎鍊兼潵鏇存柊涓€娆℃潈閲嶏紝鐒跺悗鍒╃敤鏇存柊鍚庣殑鏉冮噸杩涜涓嬩竴杞殑璁＄畻锛岃繖绉嶆柟娉曞彨鎵归噺姊害涓嬮檷(Batch Gradient Descent)銆?/p>
Andrew Ng鐨勩€婃満鍣ㄥ涔犮€嬪叕寮€璇? https://class.coursera.org/ml 闃呰杩囨湰鏂囩殑浜鸿繕鐪嬩簡浠ヤ笅锛?/strong> 涓嶆柇鏇存柊璧勬簮 娣卞害瀛︿範銆佹満鍣ㄥ涔犮€佹暟鎹垎鏋愩€乸ython 以上是关于鍏ラ棬娣卞害瀛︿範锛岀悊瑙ｇ缁忕綉缁溿€佸弽鍚戜紶鎾畻娉曟槸绗竴鍏?/h1>
Coursera鍏紑璇剧瑪璁颁腑鏂囩増锛堢缁忕綉缁滅殑琛ㄧず锛? http://52opencourse.com/139/coursera鍏紑璇剧瑪璁?鏂潶绂忓ぇ瀛︽満鍣ㄥ涔犵鍏-绁炵粡缃戠粶鐨勮〃绀?neural-networks-representation
Coursera鍏紑璇捐棰戯紙绁炵粡缃戠粶鐨勫涔狅級: http://52opencourse.com/289/coursera鍏紑璇捐棰?鏂潶绂忓ぇ瀛︽満鍣ㄥ涔犵涔濊-绁炵粡缃戠粶鐨勫涔?neural-networks-learning
鏂潶绂忔繁搴﹀涔犱腑鏂囩増锛?http://deeplearning.stanford.edu/wiki/index.php/UFLDL鏁欑▼