Given a target vector and a feature vector, how to computer the weight












1












$begingroup$


In page 13 of the slide, given $t$ and $X$ as following. I don't understand how we get $w$.



$$t=[t^{(1)},t^{(2)}, ldots, t^{(N)} ]^T$$
$$X=begin{bmatrix}1, x^{(1)} \ 1, x^{(2)} \ vdots\1, x^{(N)} end{bmatrix}$$




  • Then:


$$w=(X^TX)^{-1}X^Tt$$










share|improve this question









New contributor




user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$

















    1












    $begingroup$


    In page 13 of the slide, given $t$ and $X$ as following. I don't understand how we get $w$.



    $$t=[t^{(1)},t^{(2)}, ldots, t^{(N)} ]^T$$
    $$X=begin{bmatrix}1, x^{(1)} \ 1, x^{(2)} \ vdots\1, x^{(N)} end{bmatrix}$$




    • Then:


    $$w=(X^TX)^{-1}X^Tt$$










    share|improve this question









    New contributor




    user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















      1












      1








      1





      $begingroup$


      In page 13 of the slide, given $t$ and $X$ as following. I don't understand how we get $w$.



      $$t=[t^{(1)},t^{(2)}, ldots, t^{(N)} ]^T$$
      $$X=begin{bmatrix}1, x^{(1)} \ 1, x^{(2)} \ vdots\1, x^{(N)} end{bmatrix}$$




      • Then:


      $$w=(X^TX)^{-1}X^Tt$$










      share|improve this question









      New contributor




      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      In page 13 of the slide, given $t$ and $X$ as following. I don't understand how we get $w$.



      $$t=[t^{(1)},t^{(2)}, ldots, t^{(N)} ]^T$$
      $$X=begin{bmatrix}1, x^{(1)} \ 1, x^{(2)} \ vdots\1, x^{(N)} end{bmatrix}$$




      • Then:


      $$w=(X^TX)^{-1}X^Tt$$







      machine-learning






      share|improve this question









      New contributor




      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question









      New contributor




      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




      share|improve this question








      edited 3 hours ago









      Siong Thye Goh

      1,177418




      1,177418






      New contributor




      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked 5 hours ago









      user8314628user8314628

      1083




      1083




      New contributor




      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.





      New contributor





      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      user8314628 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






















          1 Answer
          1






          active

          oldest

          votes


















          2












          $begingroup$

          The least square problem is to minimize $$|Xw-t|^2$$



          Differentiating it with respect to $w$ and equating it to $0$, we have



          $$2X^T(Xw-t)=0$$



          Hence, we have



          $$X^TXw-X^Tt=0$$



          That is $$X^TXw=X^Tt$$



          $$w=(X^TX)^{-1}X^Tt$$






          share|improve this answer









          $endgroup$













            Your Answer





            StackExchange.ifUsing("editor", function () {
            return StackExchange.using("mathjaxEditing", function () {
            StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
            StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
            });
            });
            }, "mathjax-editing");

            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "557"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: false,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: null,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });






            user8314628 is a new contributor. Be nice, and check out our Code of Conduct.










            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f46114%2fgiven-a-target-vector-and-a-feature-vector-how-to-computer-the-weight%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2












            $begingroup$

            The least square problem is to minimize $$|Xw-t|^2$$



            Differentiating it with respect to $w$ and equating it to $0$, we have



            $$2X^T(Xw-t)=0$$



            Hence, we have



            $$X^TXw-X^Tt=0$$



            That is $$X^TXw=X^Tt$$



            $$w=(X^TX)^{-1}X^Tt$$






            share|improve this answer









            $endgroup$


















              2












              $begingroup$

              The least square problem is to minimize $$|Xw-t|^2$$



              Differentiating it with respect to $w$ and equating it to $0$, we have



              $$2X^T(Xw-t)=0$$



              Hence, we have



              $$X^TXw-X^Tt=0$$



              That is $$X^TXw=X^Tt$$



              $$w=(X^TX)^{-1}X^Tt$$






              share|improve this answer









              $endgroup$
















                2












                2








                2





                $begingroup$

                The least square problem is to minimize $$|Xw-t|^2$$



                Differentiating it with respect to $w$ and equating it to $0$, we have



                $$2X^T(Xw-t)=0$$



                Hence, we have



                $$X^TXw-X^Tt=0$$



                That is $$X^TXw=X^Tt$$



                $$w=(X^TX)^{-1}X^Tt$$






                share|improve this answer









                $endgroup$



                The least square problem is to minimize $$|Xw-t|^2$$



                Differentiating it with respect to $w$ and equating it to $0$, we have



                $$2X^T(Xw-t)=0$$



                Hence, we have



                $$X^TXw-X^Tt=0$$



                That is $$X^TXw=X^Tt$$



                $$w=(X^TX)^{-1}X^Tt$$







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered 3 hours ago









                Siong Thye GohSiong Thye Goh

                1,177418




                1,177418






















                    user8314628 is a new contributor. Be nice, and check out our Code of Conduct.










                    draft saved

                    draft discarded


















                    user8314628 is a new contributor. Be nice, and check out our Code of Conduct.













                    user8314628 is a new contributor. Be nice, and check out our Code of Conduct.












                    user8314628 is a new contributor. Be nice, and check out our Code of Conduct.
















                    Thanks for contributing an answer to Data Science Stack Exchange!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    Use MathJax to format equations. MathJax reference.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f46114%2fgiven-a-target-vector-and-a-feature-vector-how-to-computer-the-weight%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    Сан-Квентин

                    Алькесар

                    Josef Freinademetz