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author | Yuchen Pei <me@ypei.me> | 2018-12-02 22:17:29 +0100 |
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committer | Yuchen Pei <me@ypei.me> | 2018-12-02 22:17:29 +0100 |
commit | 52fbfc6b9bf7aae292466e2e7b67d3d419da59dd (patch) | |
tree | 5241441df3b18ce27c5558c4b4dcde1f308cdaf8 | |
parent | c6da915fe94b57390eb746f9708df9c6ea058094 (diff) |
minor change
-rw-r--r-- | posts/2018-12-02-lime-shapley.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/posts/2018-12-02-lime-shapley.md b/posts/2018-12-02-lime-shapley.md index 1f1fe34..5ccf701 100644 --- a/posts/2018-12-02-lime-shapley.md +++ b/posts/2018-12-02-lime-shapley.md @@ -76,8 +76,8 @@ feature contributions of supervised learning models locally. Let $f: X_1 \times X_2 \times ... \times X_n \to \mathbb R$ be a function. We can think of $f$ as a model, where $X_j$ is the space of -$j$th feature. For example, in a language model, $X_j$ may be the count -of the $j$th word in the vocabulary. +$j$th feature. For example, in a language model, $X_j$ may correspond to +the count of the $j$th word in the vocabulary. The output may be something like housing price, or log-probability of something. |