CS256
Chris Pollett
Oct 11, 2017
What kind of hypothesis we have is dependent on the things we can actually measure with an NN experiment. On the next few slides I give some examples of the kinds of things we can measure. After this, I give some example hypothesis which could be tested using these kind of experiments.
TPR | FPR |
FNR | TNR |
Observed Label | ||||
---|---|---|---|---|
A | B | C | ||
Predicted Label | A | 5 | 1 | 2 |
B | 3 | 7 | 4 | |
C | 0 | 2 | 9 |
pip install matplotlib
import matplotlib.pyplot as plt import numpy as np a = np.arange(0, 10,.5, dtype=float); b = a * a plt.title("The function y=x^2") plt.xlabel("x-axis") plt.ylabel("y-axis") plt.plot(a,b) plt.show()
import matplotlib.pyplot as plt import numpy as np a = np.arange(0, 10,.5, dtype=float); plt.title("Growth rates y=x, y=x^2, and y=x^3") plt.xlabel("x-axis") plt.ylabel("y-axis") id_line, = plt.plot(a,a, color="blue", label="y=x", linestyle='dashed', linewidth=2) quad_line, = plt.plot(a, a**2, color="red", label="y=x^2", linestyle='dotted') cube_line, = plt.plot(a, a**3, color="green", label="y=x^2", linestyle='dashdot') plt.legend(handles=[id_line, quad_line, cube_line], loc=2) #loc can be a number 1-4, number represents #which corner plt.show()
import matplotlib.pyplot as plt import numpy as np a = np.arange(0, 10,.5, dtype=float); plt.title("Various polynomials") plt.xlabel("x-axis") plt.ylabel("y-axis") plt.scatter(a, a**2) plt.scatter(a, a**3, marker="+", color="green"); plt.scatter(a, a**4, 200, marker="o"); # 200 is size in pixels plt.show()
import matplotlib.pyplot as plt import numpy as np a = np.array([1,1,2,2,2,2,3,4,4,4,4, 5,5,5,5,6,6,7,8,8,9,9,9,10,10,10]) plt.hist(a, bins=5) plt.show();
import matplotlib.pyplot as plt import numpy as np plt.title("Product Comparison") plt.bar(["Product A", "Product B"], [50, 100]) plt.show();
import matplotlib.pyplot as plt import numpy as np plt.title("Marketshare Comparison") companies = ["Company A", "Company B", "Company C"] shares = [20, 50, 30] colors = ['red', 'green', 'blue'] plt.pie(shares, labels=companies, colors=colors, startangle=100) plt.show();
import matplotlib.pyplot as plt plt.title("Product Comparison") plt.bar(["Product A", "Product B"], [50, 100]) plt.draw(); plt.savefig("product_comparison.png");