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Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 1)

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Kirill Eremenko

Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 1)

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© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Visible Input Nodes Visible Output Nodes (Map) X1 X3 X2
© SuperDataScienceDeep Learning A-Z Visible Input Nodes Visible Output Nodes X1 X3 X2
© SuperDataScienceDeep Learning A-Z Visible Input Nodes Visible Output Nodes X1 X3 X2 W1,1 W1,2 W1,3
© SuperDataScienceDeep Learning A-Z ( ; ; ) Visible Input Nodes Visible Output Nodes X1 X3 X2 W1,1 W1,2 W1,3Node1:
© SuperDataScienceDeep Learning A-Z ( ; ; ) Visible Input Nodes Visible Output Nodes X1 X3 X2 W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2:
© SuperDataScienceDeep Learning A-Z ( ; ; ) Visible Input Nodes Visible Output Nodes X1 X3 X2 W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3:
© SuperDataScienceDeep Learning A-Z ( ; ; ) Visible Input Nodes X3 W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: X2 X1
© SuperDataScienceDeep Learning A-Z ( ; ; )W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: ( ; ; )W5,1 W5,2 W5,3Node5: ( ; ; )W6,1 W6,2 W6,3Node6: ( ; ; )W7,1 W7,2 W7,3Node7: ( ; ; )W8,1 W8,2 W8,3Node8: ( ; ; )W9,1 W9,2 W9,3Node9: Distance = (𝑥𝑖 − 𝑤1,𝑖)2 = 1.2 X3 X2 X1
© SuperDataScienceDeep Learning A-Z ( ; ; )W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: ( ; ; )W5,1 W5,2 W5,3Node5: ( ; ; )W6,1 W6,2 W6,3Node6: ( ; ; )W7,1 W7,2 W7,3Node7: ( ; ; )W8,1 W8,2 W8,3Node8: ( ; ; )W9,1 W9,2 W9,3Node9: Distance = (𝑥𝑖 − 𝑤1,𝑖)2 = 1.2 Distance = (𝑥𝑖 − 𝑤2,𝑖)2 = 0.8 X3 X2 X1
© SuperDataScienceDeep Learning A-Z ( ; ; )W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: ( ; ; )W5,1 W5,2 W5,3Node5: ( ; ; )W6,1 W6,2 W6,3Node6: ( ; ; )W7,1 W7,2 W7,3Node7: ( ; ; )W8,1 W8,2 W8,3Node8: ( ; ; )W9,1 W9,2 W9,3Node9: Distance = (𝑥𝑖 − 𝑤1,𝑖)2 = 1.2 Distance = (𝑥𝑖 − 𝑤2,𝑖)2 = 0.8 Distance = (𝑥𝑖 − 𝑤3,𝑖)2 = 0.4 X3 X2 X1
© SuperDataScienceDeep Learning A-Z ( ; ; )W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: ( ; ; )W5,1 W5,2 W5,3Node5: ( ; ; )W6,1 W6,2 W6,3Node6: ( ; ; )W7,1 W7,2 W7,3Node7: ( ; ; )W8,1 W8,2 W8,3Node8: ( ; ; )W9,1 W9,2 W9,3Node9: Distance = (𝑥𝑖 − 𝑤1,𝑖)2 = 1.2 Distance = (𝑥𝑖 − 𝑤2,𝑖)2 = 0.8 Distance = (𝑥𝑖 − 𝑤3,𝑖)2 = 0.4 Distance = (𝑥𝑖 − 𝑤4,𝑖)2 = 1.1 X3 X2 X1
© SuperDataScienceDeep Learning A-Z ( ; ; )W1,1 W1,2 W1,3Node1: ( ; ; )W2,1 W2,2 W2,3Node2: ( ; ; )W3,1 W3,2 W3,3Node3: ( ; ; )W4,1 W4,2 W4,3Node4: ( ; ; )W5,1 W5,2 W5,3Node5: ( ; ; )W6,1 W6,2 W6,3Node6: ( ; ; )W7,1 W7,2 W7,3Node7: ( ; ; )W8,1 W8,2 W8,3Node8: ( ; ; )W9,1 W9,2 W9,3Node9: Distance = (𝑥𝑖 − 𝑤1,𝑖)2 = 1.2 Distance = (𝑥𝑖 − 𝑤2,𝑖)2 = 0.8 Distance = (𝑥𝑖 − 𝑤3,𝑖)2 = 0.4 Distance = (𝑥𝑖 − 𝑤4,𝑖)2 = 1.1 Distance = (𝑥𝑖 − 𝑤5,𝑖)2 = 1.3 Distance = (𝑥𝑖 − 𝑤6,𝑖)2 = 1.0 Distance = (𝑥𝑖 − 𝑤7,𝑖)2 = 0.6 Distance = (𝑥𝑖 − 𝑤8,𝑖)2 = 1.2 Distance = (𝑥𝑖 − 𝑤9,𝑖)2 = 0.9 X3 X2 X1
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Image Source: Wikipedia
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z

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