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@@ -40,7 +40,7 @@ Here, the `Count()` function represents "counting":
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- $Count(w_{i−1},w_i)$: represents the total number of times the word pair $(w_{i−1},w_i)$ appears consecutively in the corpus.
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- $Count(w_{i−1})$: represents the total number of times the single word $w_{i−1}$ appears in the corpus.
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-The formula's meaning is: we use "the number of times word pair $Count(w_i−1,w_i)$ appears" divided by "the total number of times word $Count(w_{i−1})$ appears" as an approximate estimate of $P(w_i∣w_{i−1})$.
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+The formula's meaning is: we use "the number of times word pair $Count(w_{i−1},w_i)$ appears" divided by "the total number of times word $Count(w_{i−1})$ appears" as an approximate estimate of $P(w_i∣w_{i−1})$.
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To make this process more concrete, let's manually perform a calculation. Suppose we have a mini corpus containing only the following two sentences: `datawhale agent learns`, `datawhale agent works`. Our goal is: using a Bigram (N=2) model, estimate the probability of the sentence `datawhale agent learns` appearing. According to the Bigram assumption, we examine consecutive pairs of words (i.e., word pairs) each time.
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