September 2017
Beginner to intermediate
304 pages
7h 2m
English
Content preview from Machine Learning With Go
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Profiling the data
Yes, you guessed it! We have a new dataset and we need to profile this dataset to learn a little more about it. Let's first calculate summary statistics with github.com/kniren/dataframe and create histograms of each feature using gonum.org/v1/plot. We have already done this multiple times in Chapter 4, Regression and Chapter 5, Classification, so we will not rehash the code here. Let's just look at the results:
$ go build $ ./myprogram [7x4] DataFrame column Driver_ID Distance_Feature Speeding_Feature 0: mean 3423312447.500000 76.041523 10.721000 1: stddev 1154.844867 53.469563 13.708543 2: min 3423310448.000000 15.520000 0.000000 3: 25% 3423311447.000000 45.240000 4.000000 4: 50% 3423312447.000000 53.330000 6.000000 5: ...
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