8 Jun 2016 . Sencha Architect 3.2 Free Download for Windows. We provide fast and easy to use software. Sencha Architect (Sencha Architect Download).
Sencha Architect 3.2 (Build 320) Free Download is a free software product developed by Sencha Inc. This site is not a mirror of any external sites. Sencha Architect 3.2 Free Download.
10 Oct 2011 The main theme of Sencha Architect 3.2 is “Most Common Platforms” and is fully compatible with major . Sencha Architect 3.2 Build 320 - Internet-based platform supporting the Sencha framework and a wide range of other cross-platform.
Sencha Architect 3.2 Build 320 is a professional web application solution provider is fully compatible with major web browsers and mobile devices. Sencha Architect 3.2 build 320 PC Download.
Sencha Architect is a cross-platform application builder used to build HTML5 mobile and web applications. Sencha Architect (Sencha Architect Download).Q:
Is it possible to identify a country in a Machine Learning classification?
I have a dataset that contains numbers in different categories and is split into 50/50 train and test sets. One of the categories is country. When I get the data from the database, the country is automatically identified.
Is it possible to use that information to train a machine learning classifier?
A:
Of course it is! One very simple example would be that you could split the dataset into countries (but not 50/50), and let's assume you have around 100 records for each country. Training a naive Bayes classifier using a maximum entropy approach (e.g. scikit-learn) would have the following as training example:
Feature: Country
Label: country
Value: France
Feature: Country
Label: Spain
Value: USA
(the obvious thing to do, of course, would be to normalize the data into ranges such as 0-1, 0-100, etc.)
The test example would look like this:
Feature: Country
Label: country
Value: France
Feature: Country
Label: Spain
Value: France
Training would use the labels provided, and the classifier would predict the probability of a French person belonging to each country.
I don't know how you are using the country label in your classification, but using it in a naive Bayes classifier be359ba680
Related links:
Komentarze