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--- med:lab_2 [2019/03/12 16:04]
pszwed [Knowledge Explorer]
+++ med:lab_2 [2022/03/06 23:01]
pszwed [Knowledge Explorer]
@@ Line 1: / Line 1: @@
-===== Metody Eksploracji Danych: Laboratorium 2 =====
+===== Eksploracja Danych: Laboratorium 2 =====
  {{:med:med-lab02.pdf|Opis zadań (PDF)}}
@@ Line 22: / Line 22: @@
   *Argumenty przekształceń
-     *Copy - ''1'' lub ''first''
+       *Copy - ''1'' lub ''first''
-     *Rename Find: ''Copy of X'' replace: ''X2''
+       *Rename Find: ''Copy of X'' replace: ''X2''
-     *Reorder  - podaje permutację, czyli ''1,3,2''
+       *Reorder  - podaje permutację, czyli ''1,3,2''
-     *MathExpression: expression: ''A*A'' ,ignore range ''1,3''
+       *MathExpression: expression: ''A*A'' ,ignore range ''1,3''
@@ Line 47: / Line 47: @@
   * Punkt 2.5 :!: W tej wersji Weka grupowanie nie działa
+---
+<code python>
+from keras import layers
+from keras import models
+from keras.models import Sequential,InputLayer
+from keras.layers import Dense
+from io import StringIO
+import tensorflow as tf
+import matplotlib.pyplot as plt
+import numpy as np
+# 005.arff
+data = """
+-4.84295,-27.856212
+...
+"""
+#enter data as a string
+inp =  StringIO(data)
+x, y = np.loadtxt(inp, delimiter=',', usecols=(0, 1), unpack=True,skiprows=0)
+X = np.stack((x,x**2,x**3),axis=-1)
+tf.random.set_seed(1)
+model = models.Sequential()
+model.add(layers.InputLayer(input_shape=(X.shape[1],)))
+model.add(layers.Dense(1))
+model.summary()
+model.compile(optimizer=tf.keras.optimizers.RMSprop(????), loss='mse', metrics=['mse','mae'])
+hist = model.fit(X,y,epochs=???,verbose=1)
+y_pred = model.predict(X)
+plt.scatter(x,y)
+plt.plot(x,(x+4)*(x+1)*(x-3),c='g')
+plt.plot(x,y_pred,c='r')
+</code>