Probabilistic Modeling

$X_1,··· ,X_n$ where $X_i ∼ binomial(n, p)$, $∀i ∈ [1,n]$, and where p is the parameter of interest?

2. Define the term non-informative prior.

1. How do MPE and MAP differ?
2. Give an example of when they would produce different results.

1. How is Naive Bayes classifier naive?
2. Let’s try to construct a Naive Bayes classifier to classify whether a tweet has a positive or negative sentiment. We have four training samples: $\begin{bmatrix} \text{Tweet} & \text{Label} \\\\ \text{This makes me so upset} & \text{Negative}\\\\ \text{This puppy makes me happy} & \text{Positive} \\\\ \text{Look at this happy hamster} & \text{Positive} \\\\ \text{No hamsters allowed in my house} & \text{Negative} \end{bmatrix}$ According to your classifier, what's sentiment of the sentence The hamster is upset with the puppy?