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If null is generated.\nvar context = {\n weightSeq: null\n};\n\n// \"matrix\" is a list of weights to apply. If the length of the \"matrix\" list is different from the total \"matrix weights\", it will be ignored and \"context.weightSeq\" will be used.\nvar matrix = [];\n\n// \"input\" data to input\nvar input = [1, 5, 20, 4, 204, 43];\n\n// \"hiddenColumn\" hidden columns of neurons\nvar hiddenColumn = 3;\n\n// \"hiddenRow\" hidden rows of neurons\nvar hiddenRow = 4;\n\n// \"outputColumns\" output options. Return array integer 0 or 1, ex: [1, 0, 1]\nvar outputColumns = 3;\n\n// \"outputData\" is a callback function to see output result\nvar outputData = function(output) {\n console.log(output); // ex: [1, 0, 1]\n}\n\n// Execute neural network\nNeuralNetwork.exec(context, matrix, input, hiddenColumn, hiddenRow, outputColumns, outputData);\n```","readmeFilename":"README.md"}