Sample of data set (head, tail, random):
  sepal_length sepal_width petal_length petal_width        class
0          5.1         3.5          1.4         0.2  Iris-setosa
1          4.9         3.0          1.4         0.2  Iris-setosa
2          4.7         3.2          1.3         0.2  Iris-setosa
3          4.6         3.1          1.5         0.2  Iris-setosa
4          5.0         3.6          1.4         0.2  Iris-setosa
    sepal_length sepal_width petal_length petal_width           class
145          6.7         3.0          5.2         2.3  Iris-virginica
146          6.3         2.5          5.0         1.9  Iris-virginica
147          6.5         3.0          5.2         2.0  Iris-virginica
148          6.2         3.4          5.4         2.3  Iris-virginica
149          5.9         3.0          5.1         1.8  Iris-virginica
    sepal_length sepal_width petal_length petal_width            class
107          7.3         2.9          6.3         1.8   Iris-virginica
146          6.3         2.5          5.0         1.9   Iris-virginica
85           6.0         3.4          4.5         1.6  Iris-versicolor
4            5.0         3.6          1.4         0.2      Iris-setosa
82           5.8         2.7          3.9         1.2  Iris-versicolor
statistical summary:
       sepal_length sepal_width petal_length petal_width        class
count           150         150          150         150          150
unique           35          23           43          22            3
top             5.0         3.0          1.5         0.2  Iris-setosa
freq             10          26           14          28           50
Null count:
sepal_length    0
sepal_width     0
petal_length    0
petal_width     0
class           0
dtype: int64
Sample development test set results using scoring method 'accuracy'
Cross validation results over development test set
name	acc	stdev
LR	0.958	0.056
Results over validation data for LR:
validation confusion matrix:
[[10  0  0]
 [ 0  8  0]
 [ 0  0 12]]
classification report:
                 precision    recall  f1-score   support

    Iris-setosa       1.00      1.00      1.00        10
Iris-versicolor       1.00      1.00      1.00         8
 Iris-virginica       1.00      1.00      1.00        12

       accuracy                           1.00        30
      macro avg       1.00      1.00      1.00        30
   weighted avg       1.00      1.00      1.00        30

