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I am working on a clustering problem. I have 11 features. My complete data frame has 70-80% zeros. The data had outliers that I capped at 0.5 and 0.95 percentile. However, I tried k-means (python) on data and received a very unusual cluster that looks like a cuboid. I am not sure if this result is
我使用Azure客户端库执行批量插入到Azure表存储中。一切都很好。但是当我使用Fiddler嗅探请求时,我发现来自azure的每个响应都是90 is左右。我已经更改了首选标题,而不是“返回-无内容”,但响应仍然超过60 to (当请求为50 to)。
有没有办法减少反应的长度?就像100 B (HTTP 202或什么的)。
我有一个AJAX函数来发送参数并从python脚本中检索一些json对象。我尝试将输入文本中的值发送到脚本
AJAX代码
function ajax_get_json(){
var results = document.getElementById("results");
var hr = new XMLHttpRequest();
var tipo = document.getElementById('tipo').value;
var atributo = " " +tipo;
document.get