From 175ac10904d0f31c3ffeeeed507c8914f13d0b15 Mon Sep 17 00:00:00 2001 From: leshe4ka46 Date: Sat, 13 Dec 2025 19:41:40 +0300 Subject: linr, logr --- R_LogR/mlclass-ex2/predict.m | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) create mode 100644 R_LogR/mlclass-ex2/predict.m (limited to 'R_LogR/mlclass-ex2/predict.m') diff --git a/R_LogR/mlclass-ex2/predict.m b/R_LogR/mlclass-ex2/predict.m new file mode 100644 index 0000000..7af3a20 --- /dev/null +++ b/R_LogR/mlclass-ex2/predict.m @@ -0,0 +1,32 @@ +function p = predict(theta, X) +%PREDICT Predict whether the label is 0 or 1 using learned logistic +%regression parameters theta +% p = PREDICT(theta, X) computes the predictions for X using a +% threshold at 0.5 (i.e., if sigmoid(theta'*x) >= 0.5, predict 1) + +m = size(X, 1); % Number of training examples + +% You need to return the following variables correctly +p = zeros(m, 1); + +% ====================== YOUR CODE HERE ====================== +% Instructions: Complete the following code to make predictions using +% your learned logistic regression parameters. +% You should set p to a vector of 0's and 1's +% +thresh = 0.5 + +pred = sigmoid(X * theta); +for i = 1:m + if pred(i) >= thresh + p(i) = 1; + else + p(i) = 0; + endif + + + +% ========================================================================= + + +end -- cgit v1.2.3