machine learning - Feature Normalization -


in statistics hardly ever feature normalization. center covariates when needed, don't normalization. in machine learning, deep learning feature normalization paramount. why important in application, not important in others.

for machine learning approaches scaling important because influence computation of objective function.

for example, many algorithms use euclidean distance classification, if have feature has values bigger other features, dominate distance , predictions influenced sole feature.

scaling helps gradient descend (method used in many algorithms minimize error function) converge faster. svms train faster normalized values.

in summary, having values on same scale helps computation. guess why important on machine learning , not necessary on statistics machine learning algorithms have loops iterate many times. @ each iteration values "out of scale" influence more , more, dominating model. on other hand statistic methods don't have these loops, scaling doesn't affect much.


Comments

Post a Comment

Popular posts from this blog

How to understand 2 main() functions after using uftrace to profile the C++ program? -

i trying uftrace profile following simple c++ program: #include <iostream> class { public: a() {std::cout << "a created" << std::endl;} ~a() {std::cout << "a destroyed" << std::endl;} }; int main() { a; return 0; } the profile result this: # uftrace a.out created destroyed # duration tid function 2.026 [ 4828] | __cxa_atexit(); [ 4828] | main() { [ 4828] | __static_initialization_and_destruction_0() { 89.397 [ 4828] | std::ios_base::init::init(); 0.768 [ 4828] | __cxa_atexit(); 93.029 [ 4828] | } /* __static_initialization_and_destruction_0 */ 94.425 [ 4828] | } /* main */ [ 4828] | main() { [ 4828] | a::a() { 11.104 [ 4828] | std::operator <<(); 10.825 [ 4828] | std::basic_ostream::operator <<(); 24.514 [ 4828] | } /* a::a */ [ 4828] | a::~a() { 0.978 [ 4828] | ...
Read more

c# - Update a combobox from a presenter (MVP) -

i using mvp in project, new in mvp. have 2 comboboxes. when select option in combobox, combobox should filled new data. this action in presenter. view 'view1' in presenter, , introduced combobox1 , combobox2 properties in 'view1', because need 'datasource', 'displaymember', 'valuemember' , 'refresh()' in method below. but, when using pattern, enough send property like public string combobox2 { { return combobox1.selectedvalue.tosstring(); } } into presenter not whole combobox. how can solve problem? public void onselectedindexchangedcombobox1() { if (view1.combobox1.selectedindex == -1) { return; } datatable dt = tools.getdatatable("a path"); var query = (from o in dt.asenumerable() o.field<string>("afield") == farmerview.combobox1.selectedvalue.tostring() orderby o.field<string>("anotherfield") select...
Read more

How to put a lock and transaction on table using spring 4 or above using jdbcTemplate and annotations like @Transactional? -

i trying put lock on table while writing on table , if happened in between roll-back . trying convert below code lock table test_g1 read; lock table test_g write; -- begin; start transaction; insert test_g1 values(143); insert test_g values(145); select * test_g1; select * test_g; rollback; select * test_g; unlock tables; how convert above code @transactional spring jdbctemplate code? @transactional(rollbackfor={dataaccessexception.class}) public void test(){ jdbctemplate.execute("insert test1 (id, nam) values (4, 'a')"); throw new dataaccessexception("error") { }; } here trying throw error, insert statement should rollback it's not happening . thanks edit-1 attaching code , doing in jdbcdaoimpl.java , mentioned problem comment above test() . app.java package com.cgiri.javabrains.spring4; import org.springframework.beans.factory.annotation.autowired; import org.springframework.context.applic...
Read more