Course 3: Week 1 (Lab 2) problem

I was curious about last part of Lab that how can I create plot as It was created in upper part of code.

I want to create a plot as this:

but facing error like this:
Error: "ValueError Traceback (most recent call last)
4 # Visualize the fit
----> 5 visualize_fit(X_val_high, mu_high, var_high)
7 # Draw a red circle around those outliers

~/work/ in visualize_fit(X, mu, var)
45 X1, X2 = np.meshgrid(np.arange(0, 35.5, 0.5), np.arange(0, 35.5, 0.5))
—> 46 Z = multivariate_gaussian(np.stack([X1.ravel(), X2.ravel()], axis=1), mu, var)
47 Z = Z.reshape(X1.shape)

~/work/ in multivariate_gaussian(X, mu, var)
30 var = np.diag(var)
—> 32 X = X - mu
33 p = (2* np.pi)(-k/2) * np.linalg.det(var)(-0.5) *
34 np.exp(-0.5 * np.sum(np.matmul(X, np.linalg.pinv(var)) * X, axis=1))

ValueError: operands could not be broadcast together with shapes (5041,2) (11,) "

Can anyone help to solve this error. Thankyou

Ahmad Fareed Khan

Since the larger dataset has 11 features, you can’t make a 2D plot of it.

so, how can we make the plot(or any other kind of view) for lots of features like in real world examples for analysis? Is there any other method for that?

Generally you can’t plot a multi-dimensional data set. There is a plot in this assignment only so you can see how the technique works.

Thanks! Tom for guidance.