Khachmaz ( azeri: Xaçmaz) é um dos cinqüenta e nove rayones nos que subdivide politicamente a República do Azerbaijão. A cidade capital é a cidade de Xaçmaz.
Índice
1Território e População
2Economia
3Transporte
4Referências
Território e População |
Este rayon é possuidor uma superfície de 1.045 quilômetros quadrados, os quais são o lugar de uma população composta por umas 155.775 pessoas. Por onde, a densidade populacional se eleva a cifra dos 149,06 habitantes por cada quilômetro quadrado deste rayon.
Economia |
A região está dominada pela agricultura. Se cultivam verduras, frutas e cereais. Na capital, se destacam a indústria de processamento de alimentos e a indústria ligeira. Nas cidades com costas no mar Cáspio, a importância econômica depende do turismo.[1]
Transporte |
Pelo rayon de Khachmaz passa a liinha ferroviária chamada Azərbaycan Dövlət Dəmir Yolu que chega até a Federação Russa.[2]
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I found a lot of questions abount appendices and ToC. Many users want appendices to be grouped in an Appendix part, however some problems arise with ToC, hyperref, PDF viewer bookmarks, and so on. There are different solutions which require extra packages, command patching and other extra code, however none of them satisfies me. I almost found an easy way to accomplish a good result, where appendices are added to bookmarks in the right way and hyperref links point to the right page. However, the number of the "Appendix" part page is wrong (it's the number of appendix A). Is there any EASY way to fix that? This is a MWE: documentclass{book} usepackage[nottoc,notlot,notlof]{tocbibind} usepackage{hyperref} begin{document} frontmatter tableofcontents mainmatter part{First} chapter{...
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In the sklearn.model_selection.cross_val_predict page it is stated: Generate cross-validated estimates for each input data point. It is not appropriate to pass these predictions into an evaluation metric. Can someone explain what does it mean? If this gives estimate of Y (y prediction) for every Y (true Y), why can't I calculate metrics such as RMSE or coefficient of determination using these results?
python scikit-learn cross-validation
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edited Nov 28 '18 at 17:52
desertnaut
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I have written a function using curl to generate the token. I check whether the token exists; if not, then I execute the function, otherwise I skip this function and proceed to next. But I am not sure that it will work if a token is expired. Is there any command to identify the expired token and generates the new one by calling this function? #!/bin/ksh export V_TOKEN="gen_token_${V_DATE}.txt" #### Calling function to generate the token function callPOST { curl -X POST -H 'Content-Type: application/x-www-form-url' -d 'grant_type=password&username=usr01&password=pwd...
