coursera吴恩达机器学习第一到第六周octave编程作业

function J = computeCost（X y theta）
%COMPUTECOST Compute cost for linear regression
%   J = COMPUTECOST（X y theta） computes the cost of using theta as the
%   parameter for linear regression to fit the data points in X and y

% Initialize some useful values
m = length（y）; % number of training examples

% You need to return the following variables correctly 
J = 0;

% ====================== YOUR CODE HERE ======================
% Instructions: Compute the cost of a particular choice of theta
%               You should set J to the cost.

predictions = X*theta;  %X:m*2-d ; theta:2*1-d
sqrErrors = （predictions-y） .^2;
J = 1/（2*m） * sum（sqrErrors）;


% =========================================================================

end

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     文件      489928  2017-03-14 09:40  machine-learning-ex1-linear regressionex1.pdf
     目录           0  2017-12-05 14:23  machine-learning-ex1-linear regressionex1
     文件         740  2017-12-05 10:10  machine-learning-ex1-linear regressionex1computeCost.m
     文件         780  2017-12-05 14:09  machine-learning-ex1-linear regressionex1computeCostMulti.m
     文件        3908  2017-03-20 13:50  machine-learning-ex1-linear regressionex1ex1.m
     文件        4507  2017-12-05 15:32  machine-learning-ex1-linear regressionex1ex1_multi.m
     文件        1359  2017-03-14 09:40  machine-learning-ex1-linear regressionex1ex1data1.txt
     文件         657  2017-03-14 09:40  machine-learning-ex1-linear regressionex1ex1data2.txt
     文件        1365  2017-12-05 14:58  machine-learning-ex1-linear regressionex1featureNormalize.m
     文件         957  2017-12-05 10:48  machine-learning-ex1-linear regressionex1gradientDescent.m
     文件         981  2017-12-05 14:11  machine-learning-ex1-linear regressionex1gradientDescentMulti.m
     目录           0  2017-03-14 09:40  machine-learning-ex1-linear regressionex1lib
     目录           0  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlab
     文件        1624  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabAUTHORS.txt
     文件        3862  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabChangeLog.txt
     文件         881  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabjsonopt.m
     文件        1551  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabLICENSE_BSD.txt
     文件       18732  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabloadjson.m
     文件       15574  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabloadubjson.m
     文件         771  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabmergestruct.m
     文件       19369  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabREADME.txt
     文件       17462  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabsavejson.m
     文件       16123  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabsaveubjson.m
     文件        1094  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libjsonlabvarargin2struct.m
     文件        1195  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libmakeValidFieldName.m
     文件        5562  2017-03-14 09:40  machine-learning-ex1-linear regressionex1libsubmitWithConfiguration.m
     文件         669  2017-12-05 15:31  machine-learning-ex1-linear regressionex1
ormalEqn.m
     文件        6293  2017-12-05 14:23  machine-learning-ex1-linear regressionex1octave-workspace
     文件         982  2017-12-05 09:31  machine-learning-ex1-linear regressionex1plotData.m
     文件        1876  2017-03-14 09:40  machine-learning-ex1-linear regressionex1submit.m
     文件        3098  2017-12-06 14:37  machine-learning-ex1-linear regressionex1 est.m
............此处省略176个文件信息