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1320 lines
162 KiB
1320 lines
162 KiB
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# A simple neural network with one hidden layer in pure Python"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## A simple neural network class with ReLU activation function"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 77,
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"metadata": {},
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"outputs": [],
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"source": [
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"# A simple feed-forward neutral network with on hidden layer\n",
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"# see also https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"class NeuralNetwork:\n",
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" def __init__(self, x, y):\n",
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" n1 = 4 # number of neurons in the hidden layer\n",
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" self.input = x\n",
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" self.weights1 = np.random.rand(self.input.shape[1],n1)\n",
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" self.bias1 = np.random.rand(n1)\n",
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" self.weights2 = np.random.rand(n1,1)\n",
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" self.bias2 = np.random.rand(1) \n",
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" self.y = y\n",
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" self.output = np.zeros(y.shape)\n",
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" self.learning_rate = 0.00001\n",
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" self.n_train = 0\n",
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" self.loss_history = []\n",
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"\n",
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" def relu(self, x):\n",
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" return np.where(x>0, x, 0)\n",
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" \n",
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" def relu_derivative(self, x):\n",
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" return np.where(x>0, 1, 0)\n",
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"\n",
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" def feedforward(self):\n",
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" self.layer1 = self.relu(self.input @ self.weights1 + self.bias1)\n",
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" self.output = self.relu(self.layer1 @ self.weights2 + self.bias2)\n",
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"\n",
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" def backprop(self):\n",
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"\n",
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" # delta1: [m, 1], m = number of training data\n",
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" delta1 = 2 * (self.y - self.output) * self.relu_derivative(self.output)\n",
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"\n",
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" # Gradient w.r.t. weights from hidden to output layer: [n1, 1] matrix, n1 = # neurons in hidden layer\n",
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" d_weights2 = self.layer1.T @ delta1\n",
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" d_bias2 = np.sum(delta1) \n",
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" \n",
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" # shape of delta2: [m, n1], m = number of training data, n1 = # neurons in hidden layer\n",
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" delta2 = (delta1 @ self.weights2.T) * self.relu_derivative(self.layer1)\n",
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" d_weights1 = self.input.T @ delta2\n",
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" d_bias1 = np.ones(delta2.shape[0]) @ delta2 \n",
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" \n",
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" # update weights and biases\n",
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" self.weights1 += self.learning_rate * d_weights1\n",
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" self.weights2 += self.learning_rate * d_weights2\n",
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"\n",
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" self.bias1 += self.learning_rate * d_bias1\n",
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" self.bias2 += self.learning_rate * d_bias2\n",
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"\n",
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" def train(self, X, y):\n",
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" self.output = np.zeros(y.shape)\n",
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" self.input = X\n",
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" self.y = y\n",
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" self.feedforward()\n",
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" self.backprop()\n",
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" self.n_train += 1\n",
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" if (self.n_train %1000 == 0):\n",
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" loss = np.sum((self.y - self.output)**2)\n",
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" print(\"loss: \", loss)\n",
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" self.loss_history.append(loss)\n",
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" \n",
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" def predict(self, X):\n",
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" self.output = np.zeros(y.shape)\n",
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" self.input = X\n",
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" self.feedforward()\n",
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" return self.output\n",
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" \n",
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" def loss_history(self):\n",
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" return self.loss_history\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Create toy data\n",
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"We create three toy data sets\n",
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"1. two moon-like distributions\n",
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"2. circles\n",
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"3. linearly separable data sets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 78,
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"metadata": {},
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"outputs": [],
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"source": [
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"# https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html#sphx-glr-auto-examples-classification-plot-classifier-comparison-py\n",
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"import numpy as np\n",
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"from sklearn.datasets import make_moons, make_circles, make_classification\n",
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"from sklearn.model_selection import train_test_split\n",
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"\n",
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"X, y = make_classification(\n",
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" n_features=2, n_redundant=0, n_informative=2, random_state=1, n_clusters_per_class=1\n",
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")\n",
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"rng = np.random.RandomState(2)\n",
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"X += 2 * rng.uniform(size=X.shape)\n",
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"linearly_separable = (X, y)\n",
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"\n",
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"datasets = [\n",
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" make_moons(n_samples=200, noise=0.1, random_state=0),\n",
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" make_circles(n_samples=200, noise=0.1, factor=0.5, random_state=1),\n",
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" linearly_separable,\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"## Create training and test data set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 79,
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"metadata": {},
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"outputs": [],
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"source": [
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"# datasets: 0 = moons, 1 = circles, 2 = linearly separable\n",
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"X, y = datasets[1]\n",
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"X_train, X_test, y_train, y_test = train_test_split(\n",
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" X, y, test_size=0.4, random_state=42\n",
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")\n",
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"\n",
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"x_min, x_max = X[:, 0].min() - 0.5, X[:, 0].max() + 0.5\n",
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"y_min, y_max = X[:, 1].min() - 0.5, X[:, 1].max() + 0.5\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Train the model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 80,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"loss: 2.3872067282141374\n",
|
|
"loss: 2.3872058427484215\n",
|
|
"loss: 2.387205531994678\n",
|
|
"loss: 2.387205756582158\n",
|
|
"loss: 2.387205981539894\n",
|
|
"loss: 2.3872062069646356\n",
|
|
"loss: 2.387206431282743\n",
|
|
"loss: 2.387206657412996\n",
|
|
"loss: 2.3872061679858723\n",
|
|
"loss: 2.3872054613328837\n",
|
|
"loss: 2.3872056859037873\n",
|
|
"loss: 2.3872059109348127\n",
|
|
"loss: 2.387206134876376\n",
|
|
"loss: 2.387206360603658\n",
|
|
"loss: 2.3872065860311924\n",
|
|
"loss: 2.3872064904558536\n",
|
|
"loss: 2.3872054658487727\n",
|
|
"loss: 2.3872056154159624\n",
|
|
"loss: 2.387205838986268\n",
|
|
"loss: 2.3872060643164303\n",
|
|
"loss: 2.38720629000679\n",
|
|
"loss: 2.387206515465516\n",
|
|
"loss: 2.3872067402918593\n",
|
|
"loss: 2.3872057868542456\n",
|
|
"loss: 2.3872055436974926\n",
|
|
"loss: 2.387205768622451\n",
|
|
"loss: 2.3872059939050634\n",
|
|
"loss: 2.3872062189566643\n",
|
|
"loss: 2.387206443389059\n",
|
|
"loss: 2.387206669729105\n",
|
|
"loss: 2.387206114421231\n",
|
|
"loss: 2.3872054733876444\n",
|
|
"loss: 2.3872056982757286\n",
|
|
"loss: 2.3872059236497964\n",
|
|
"loss: 2.3872061471739836\n",
|
|
"loss: 2.38720637304622\n",
|
|
"loss: 2.387206597910911\n",
|
|
"loss: 2.3872064349529696\n",
|
|
"loss: 2.3872054090077848\n",
|
|
"loss: 2.3872056281842866\n",
|
|
"loss: 2.387205851329026\n",
|
|
"loss: 2.387206076790427\n",
|
|
"loss: 2.387206301261524\n",
|
|
"loss: 2.387206527494985\n",
|
|
"loss: 2.3872067526753113\n",
|
|
"loss: 2.387205728959938\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"y_train = y_train.reshape(-1, 1)\n",
|
|
"\n",
|
|
"nn = NeuralNetwork(X_train, y_train)\n",
|
|
"\n",
|
|
"for i in range(1000000):\n",
|
|
" nn.train(X_train, y_train)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot the loss vs. the number of epochs"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 83,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'loss')"
|
|
]
|
|
},
|
|
"execution_count": 83,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"plt.plot(nn.loss_history)\n",
|
|
"plt.xlabel(\"# epochs / 1000\")\n",
|
|
"plt.ylabel(\"loss\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 84,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.colorbar.Colorbar at 0x147ecf700>"
|
|
]
|
|
},
|
|
"execution_count": 84,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
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"<Figure size 900x700 with 2 Axes>"
|
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]
|
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},
|
|
"metadata": {},
|
|
"output_type": "display_data"
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}
|
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],
|
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"source": [
|
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"import matplotlib.pyplot as plt\n",
|
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"from matplotlib.colors import ListedColormap\n",
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"\n",
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"cm = plt.cm.RdBu\n",
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"cm_bright = ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
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"\n",
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"xv = np.linspace(x_min, x_max, 10)\n",
|
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"yv = np.linspace(y_min, y_max, 10)\n",
|
|
"Xv, Yv = np.meshgrid(xv, yv)\n",
|
|
"XYpairs = np.vstack([ Xv.reshape(-1), Yv.reshape(-1)])\n",
|
|
"zv = nn.predict(XYpairs.T)\n",
|
|
"Zv = zv.reshape(Xv.shape)\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(9, 7))\n",
|
|
"ax.set_aspect(1)\n",
|
|
"cn = ax.contourf(Xv, Yv, Zv, cmap=\"coolwarm_r\", alpha=0.4)\n",
|
|
"\n",
|
|
"ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright, edgecolors=\"k\")\n",
|
|
"\n",
|
|
"# Plot the testing points\n",
|
|
"ax.scatter(X_test[:, 0], X_test[:, 1], c=y_test, cmap=cm_bright, alpha=0.4, edgecolors=\"k\")\n",
|
|
"\n",
|
|
"ax.set_xlim(x_min, x_max)\n",
|
|
"ax.set_ylim(y_min, y_max)\n",
|
|
"# ax.set_xticks(())\n",
|
|
"# ax.set_yticks(())\n",
|
|
"\n",
|
|
"fig.colorbar(cn)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.9"
|
|
},
|
|
"vscode": {
|
|
"interpreter": {
|
|
"hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
|
|
}
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|