From 13f5a1f578f1ea4eff0d49bfcce43b9e571bbdb9 Mon Sep 17 00:00:00 2001 From: Chris Beaumont Date: Fri, 4 Oct 2013 07:38:06 -0400 Subject: [PATCH] underscore --- HW3.ipynb | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/HW3.ipynb b/HW3.ipynb index ddf952d..f04cf48 100644 --- a/HW3.ipynb +++ b/HW3.ipynb @@ -554,9 +554,7 @@ "Using the `critics` dataframe, compute a pair of numerical X, Y arrays where:\n", " \n", " * X is a `(nreview, nwords)` array. Each row corresponds to a bag-of-words representation for a single review. This will be the *input* to your model.\n", - " * Y is a `nreview`-element 1/0 array, encoding whether a review is Fresh (1) or Rotten (0). This is the desired *output* from your model.\n", - " \n", - "Make sure to remove items with no review text" + " * Y is a `nreview`-element 1/0 array, encoding whether a review is Fresh (1) or Rotten (0). This is the desired *output* from your model.\n" ] }, { @@ -765,7 +763,7 @@ "\n", "As discussed in lecture and HW2, a common technique for choosing appropriate values for these parameters is **cross-validation**. Let's choose good parameters by maximizing the cross-validated log-likelihood.\n", "\n", - "**3.6** Using `clf.predict_logproba`, write a function that computes the log-likelihood of a dataset" + "**3.6** Using `clf.predict_log_proba`, write a function that computes the log-likelihood of a dataset" ] }, {