Supervised learning network Multilayer Perception MLP Support Vector

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類神經網路類型 監督式學習網路(Supervised learning network) 多層感知網路(Multilayer Perception, MLP) 支援向量機(Support Vector Machine, SVM) 倒傳遞網路（Back-propagation Network, BPN）

類神經網路類型 監督式學習網路(Supervised learning network) 多層感知網路(Multilayer Perception, MLP) 支援向量機(Support Vector Machine, SVM) 倒傳遞網路（Back-propagation Network, BPN） 機率神經網路（Probabilistic Neural Network, PNN） 學習向量量化網路（Learning Vector Quantization, LVQ） 遞迴網路（Recurrent Networks, RN） 10 2020/11/25 類神經網路與財務分析

類神經網路類型 非監督式學習網路(Unsupervised learning network) 自組織映射網路（Self-Organization Map, SOM） 自適應共振理論網路（Adaptive Resonance theory Network, ART） 聯想式學習網路（Associate learning

類神經網路類型 非監督式學習網路(Unsupervised learning network) 自組織映射網路（Self-Organization Map, SOM） 自適應共振理論網路（Adaptive Resonance theory Network, ART） 聯想式學習網路（Associate learning network） 霍普菲爾網路（Hopfield Neural Network, HNN) 雙向聯想記憶網路（Bi-directional Associative Memory, BAM） 最適化應用網路（Optimization application network） 霍普菲爾-坦克網路（Hopfield-Tank Neural Network, HTN） 退火神經網路（Annealed Neural Network, ANN） 11 2020/11/25 類神經網路與財務分析

技術指標 (1)趨向指標(Durbin Watson, DW) (2)相對強弱指標(Relative Strength Indicator, RSI) 18 2020/11/25 類神經網路與財務分析

技術指標 (1)趨向指標(Durbin Watson, DW) (2)相對強弱指標(Relative Strength Indicator, RSI) 18 2020/11/25 類神經網路與財務分析

技術指標 (3)價量指標(Price Volume Indicator, PVI) (4)價量變化指標(Price Volume Change, PVC) 19 2020/11/25 類神經網路與財務分析

技術指標 (3)價量指標(Price Volume Indicator, PVI) (4)價量變化指標(Price Volume Change, PVC) 19 2020/11/25 類神經網路與財務分析

技術指標 (5)移動平均價指標(Moving Average Indicator, MAI) (6)移動平均量指標(Moving Volume Indicator, MVI) 20 2020/11/25 類神經網路與財務分析

技術指標 (5)移動平均價指標(Moving Average Indicator, MAI) (6)移動平均量指標(Moving Volume Indicator, MVI) 20 2020/11/25 類神經網路與財務分析

輸入與輸出變數 道瓊輸入變數 DW 5, DW 10, DW 20, DW 30, RSI 5, RSI 10,

輸入與輸出變數 道瓊輸入變數 DW 5, DW 10, DW 20, DW 30, RSI 5, RSI 10, RSI 20, RSI 30, PVI 5, PVI 10, PVI 20, PVI 30, PVC 5, PVC 10, PVC 20, PVC 30, MAI 5_10, MAI 5_20, MAI 5_30, MAI 10_20, MAI 10_30, MAI 20_30, MVI 5_10, MVI 5_20, MVI 5_30, MVI 10_20, MVI 10_30, MVI 20_30, PVI, NVI 共計30個輸變數 台股輸入變數 DW 5, DW 10, DW 20, DW 30, RSI 5, RSI 10, RSI 20, RSI 30, MAI 5_10, MAI 5_20, MAI 5_30, MAI 10_20, MAI 10_30, MAI 20_30, PVI, NVI 共計18個輸入變數 輸出變數 以明天的收盤價減開盤價做為計算： IF ( Close-Open ) > 0 Then “result” = 1 , Else “result” = 0 2020/11/25 類神經網路與財務分析 22

MICROSOFT OFFICE EXCEL測試方法 比較「result」與「四捨五入」是否相等，Excel函數 =IF(B 2=D 2, "True", "False") 將False顯示為 1，Excel函數=IF(E 2="False", 1, "

MICROSOFT OFFICE EXCEL測試方法 比較「result」與「四捨五入」是否相等，Excel函數 =IF(B 2=D 2, "True", "False") 將False顯示為 1，Excel函數=IF(E 2="False", 1, " ") 30 2020/11/25 類神經網路與財務分析

MICROSOFT OFFICE EXCEL測試方法 False計算次數，Excel函數=IF(F 2=1, F 2+G 1, G 1)，G 1初始 值=0 31 2020/11/25

MICROSOFT OFFICE EXCEL測試方法 False計算次數，Excel函數=IF(F 2=1, F 2+G 1, G 1)，G 1初始 值=0 31 2020/11/25 類神經網路與財務分析

MICROSOFT OFFICE EXCEL測試方法 計算總筆數「Total」，Excel函數=COUNT(D 2: D 891) 計算錯誤筆數「False」，Excel函數=COUNT(F 2: F 891) 計算正確筆數「True」，Excel函數=F 892 -F

MICROSOFT OFFICE EXCEL測試方法 計算總筆數「Total」，Excel函數=COUNT(D 2: D 891) 計算錯誤筆數「False」，Excel函數=COUNT(F 2: F 891) 計算正確筆數「True」，Excel函數=F 892 -F 893 計算錯誤率，Excel函數=F 893/F 892*100 計算正確率，Excel函數=F 894/F 892*100 32 2020/11/25 類神經網路與財務分析

UNIT3 Perception Perception Perception Perception Write a storyUNIT3 Perception Perception Perception Perception Write a story
Vector and Vector Resolution Scalar Vector Vectors VectorVector and Vector Resolution Scalar Vector Vectors Vector
Last lecture summary Multilayer perceptron MLP the mostLast lecture summary Multilayer perceptron MLP the most
Last lecture summary Multilayer perceptron MLP the mostLast lecture summary Multilayer perceptron MLP the most
MultiLayer Perceptron MLP Neural Networks Lectures 56 xMultiLayer Perceptron MLP Neural Networks Lectures 56 x
Application of MultiLayer Perceptron MLP Neural Networks inApplication of MultiLayer Perceptron MLP Neural Networks in
Neural Networks Multilayer Perceptron MLP Oscar Herrera AlcntaraNeural Networks Multilayer Perceptron MLP Oscar Herrera Alcntara
AULA 04 PERCEPTRON MULTICAMADAS MULTILAYER PERCEPTRON MLP ALGORITMOAULA 04 PERCEPTRON MULTICAMADAS MULTILAYER PERCEPTRON MLP ALGORITMO
Multilayer Perceptron MLP Regression Andrew Marshall Context InMultilayer Perceptron MLP Regression Andrew Marshall Context In
Neural Networks Perceptrons Page Multilayer Perceptron Page MLPNeural Networks Perceptrons Page Multilayer Perceptron Page MLP
Classification Supervised vs Unsupervised Learning Supervised learning classificationClassification Supervised vs Unsupervised Learning Supervised learning classification
Supervised Learning Networks Supervised Learning Networks Linear perceptronSupervised Learning Networks Supervised Learning Networks Linear perceptron
Supervised Learning Regression Ayal Gussow 1 Supervised LearningSupervised Learning Regression Ayal Gussow 1 Supervised Learning
Supervised vs Reinforcement vs Unsupervised Learning Supervised LearningSupervised vs Reinforcement vs Unsupervised Learning Supervised Learning
Chapter 4 Supervised learning Multilayer Networks II OtherChapter 4 Supervised learning Multilayer Networks II Other
Chapter 3 Supervised learning Multilayer Networks I BackpropagationChapter 3 Supervised learning Multilayer Networks I Backpropagation
Multilayer Ceramic Capacitor 1 Multilayer Ceramic Capacitor 1MLCCMultilayer Ceramic Capacitor 1 Multilayer Ceramic Capacitor 1MLCC
CONEX Main Valuable Features v Multilayer Extruder multilayerCONEX Main Valuable Features v Multilayer Extruder multilayer
Multilayer optics Problems with BraggBrentano diffractometer geometry MultilayerMultilayer optics Problems with BraggBrentano diffractometer geometry Multilayer
Support vector machines Image source Support vector machinesSupport vector machines Image source Support vector machines
Support Vector Machines 1 Support Vector Machines nSupport Vector Machines 1 Support Vector Machines n
SUPPORT VECTOR MACHINE SUPPORT VECTOR MACHINE g2 31SUPPORT VECTOR MACHINE SUPPORT VECTOR MACHINE g2 31
Support Vector Machine Contents Support Vector Machine RamyaSupport Vector Machine Contents Support Vector Machine Ramya
Support Vector Machines The support vector machine orSupport Vector Machines The support vector machine or