I’m trying to implement softmax regression using PyMC3. In this github thread @twiecki presented follwing implementatio as the correct softmax implementation using PyMC3 iris = sns.load_dataset("iris") y_2 = pd.Categorical(iris['species']).labels x_n = iris.columns[:-1] x_2 = iris[x_n].values impo…

Categorical RV takes 1d array as observation: yl = pm.Categorical('yl', p=p, observed=np.where(y_2_bin)[1])

Implementing Softmax Regresion

junpenglao July 9, 2018, 4:23am 4

Yep, it use the data to index on the first dimension of p

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