Def prob_of_X_given_C(X, features, breed, params_dict):

Course Q&A Math for Machine Learning Probability & Statistics for Machine Learning &...
1 
This is the format required by compute_training_params( )

Distribution parameters for training split:

{0: {'bark_days': params_binomial(n=30.000, p=0.801),
     'ear_head_ratio': params_uniform(a=0.100, b=0.597),
     'height': params_gaussian(mu=35.030, sigma=1.518),
     'weight': params_gaussian(mu=20.020, sigma=1.012)},

Should the parameters be in this format and not in:

{0: {'bark_days': (30.000, 0.801),
     'ear_head_ratio': (0.100, 0.597) ...

Having trouble extracting the values(mu, sigma) from params_dict when attempting prob_of_X_given_C( )

2

You have to check the output of these functions
params_uniform(a=0.100, b=0.597)… if the output is a tuple then this is how you would access dict[0][‘bark_days’][0] for the first element of the tuple.

3

So when I do that it returns;
params_uniform(a=0.100, b=0.597) as an object. Here is where I’m having trouble accessing the values 0.1 and 0.597 from params, considering how it looks in the Expected Output. Thank you

4 
@dataclass
class my_data_class:
    my_var: str
        
foo = my_data_class(my_var="Hello World")

You can access the information of my_var from foo by using the syntax foo.my_var, which should be equal to “Hello World” in this example.