def ssr_curve(self,
x,
y,
slopes=[
0.1, 0.2, 0.3, 0.4, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0,
4.0, 5.0, 7.5, 10.0
]):
ssrs = []
for slope in slopes:
yint = (np.mean(y) - slope * np.mean(x))
ssrs.append(
self.get_ss_res(zip(x, y), lambda val: slope * val + yint))
image_manager = ImageManager()
plotter = Plotter()
plotter.set_title('Sum of Squared Residuals')
plotter.set_axis_labels('Slope Selected', 'Sum of Squared Residual')
plotter.set_output_filename(g.files['ls-ssr'])
ssr_plot = ScatterSketch()
ssr_plot.add_x(slopes)
ssr_plot.add_y(ssrs)
plotter.load(ssr_plot)
plotter.save()
plotter.close()
g.debug.prn(self, 'Drawn Sum of Squared Residuals Plot')
image_manager.scale(g.files['ls-ssr'], g.files['ls-ssr'], 250)
def plot_roc(self):
plotter = Plotter()
plotter.set_title('Receiver Operating Characteristic')
plotter.set_axis_labels('')
plotter.set_output_filename() #TODO: Fill filename
plotter.close()
pass # Save the image as "roc.png"
def f_dist(self, model_type, trials):
plotter = Plotter()
image_manager = ImageManager()
plotter.set_title('F Distribution')
plotter.set_axis_labels('Frequency', 'F Score')
plotter.set_output_filename(g.files['least-squares-f'])
histogram = HistogramSketch()
for i in range(trials):
x_vals = g.randomizer.random_list(g.points_to_gen, g.lower_x_bound,
g.upper_x_bound)
y_vals = g.randomizer.random_list(g.points_to_gen, g.lower_y_bound,
g.upper_y_bound)
if model_type == LinearModel:
slope, yint = self.least_squares_slope_yint_eqn(x_vals, y_vals)
func = lambda x: slope * x + yint
else:
g.debug.prn(self, 'Incompatible model type.', 1)
break
ss_fit = self.get_ss_res(zip(x_vals, y_vals), func)
ss_mean = self.get_ss_res(zip(x_vals, y_vals),
lambda x: np.mean(x_vals))
p_fit = 2 # TODO: Update for Dataframe
p_mean = 1 # ""
n = len(x_vals)
if ss_fit == 0 or (n - p_fit) == 0 or (p_fit - p_mean) == 0:
self.debug.prn(self, 'F distribution cannot divide by zero.',
1)
continue
numerator = (ss_mean - ss_fit) / (p_fit - p_mean)
denominator = ss_fit / (n - p_fit)
histogram.add_x(numerator / denominator)
histogram.set_bins()
plotter.load(histogram)
plotter.save()
plotter.close()
image_manager.scale(g.files['least-squares-f'],
g.files['least-squares-f'], 250)
self.debug.prn(self, 'F distribution created.')