• I am analyzing and labeling some log data. (parsed already, sample data below)
  • I have extracted the major features of data.

    For examples, the classification results ("1 - normal" or "0 - anomaly") largely depends on columns "duration", "mean", "std". For example,

    • records/sec usually <= 10
    • std usually < 0.5 , etc
  • Then I want to convert current result into a prediction model, in order to classify the future log data.

Sample data:

| ID |        datetime       | No. of Records | duration(s) |  mean | std  |  labels |
| 1  |  26/7/2019 8:06:00 PM |       5        |     1.0     |  0.33 | 0.47 |  normal |
| 2  |  ...                                                                | anomaly |
| 1,000,000 |  ...                                                         |  normal |


  • How to convert such parsed & feature extracted & labelled data into a prediction mode (or prediction function)?

    I am NOT asking the theory. I have read some articles or projects of machine learning models. But many of them introduces too high-level. I still don't understand how to implement those machine learning models. I need to convert them into a real prediction function running in the computer.

    I am asking the detailed / hands-on implementation steps. Maybe it becomes a call function f(x1, x2, x3, ...) or API in the code? The new data may be the input of a function call? The output will be normal or anomaly in this case.

  • In other words, how to present a prediction model in the form of code?


1 Answer 1


This question is insanely broad… you should better go for an API documentation/tutorial... Python is usually the preferred porgramming language and two major API are used: scikit-learn for machine learning and Keras/tensorflow for Deep learning… (but there are quite a few more)

I'll give you some links... You should firstly consult these kind of sources of information and coming here later on with more specific and detailed issues.

  • $\begingroup$ yes, this is what i want the startup tips. $\endgroup$
    – TJCLK
    Commented Aug 20, 2019 at 2:05

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