Yacht Hydrodynamics (UCI, Regression, n=308, d=6)

Loading The Data

from kxy_datasets.uci_regressions import YachtHydrodynamics # pip install kxy_datasets

dataset = YachtHydrodynamics()
df = dataset.df # Retrieve the dataset as a pandas dataframe
y_column = dataset.y_column # The name of the column corresponding to the target
problem_type = dataset.problem_type # 'regression' or 'classification'

df.kxy.describe() # Visualize a summary of the data

--------------------------
Column: Beam-Draught Ratio
--------------------------
Type:   Continuous
Max:    5.3
p75:    4.2
Mean:   3.9
Median: 4.0
p25:    3.8
Min:    2.8

---------------------
Column: Froude Number
---------------------
Type:   Continuous
Max:    0.5
p75:    0.4
Mean:   0.3
Median: 0.3
p25:    0.2
Min:    0.1

-------------------------
Column: Length-Beam Ratio
-------------------------
Type:   Continuous
Max:    3.6
p75:    3.5
Mean:   3.2
Median: 3.1
p25:    3.1
Min:    2.7

---------------------------
Column: Length-Displacement
---------------------------
Type:   Continuous
Max:    5.1
p75:    5.1
Mean:   4.8
Median: 4.8
p25:    4.8
Min:    4.3

-----------------------------
Column: Longitudinal Position
-----------------------------
Type:   Continuous
Max:    0.0
p75:    -2.3
Mean:   -2.4
Median: -2.3
p25:    -2.4
Min:    -5.0

------------------------------
Column: Prismatic Coeefficient
------------------------------
Type:   Continuous
Max:    0.6
p75:    0.6
Mean:   0.6
Median: 0.6
p25:    0.5
Min:    0.5

----------------------------
Column: Residuary Resistance
----------------------------
Type:   Continuous
Max:    62
p75:    12
Mean:   10
Median: 3.1
p25:    0.8
Min:    0.0

Data Valuation

df.kxy.data_valuation(y_column, problem_type=problem_type)

[====================================================================================================] 100% ETA: 0s    Duration: 0s

	Achievable R-Squared	Achievable Log-Likelihood Per Sample	Achievable RMSE
0	0.99	-1.30	1.46

Automatic (Model-Free) Variable Selection

df.kxy.variable_selection(y_column, problem_type=problem_type)

[====================================================================================================] 100% ETA: 0s    Duration: 0s

	Variable	Running Achievable R-Squared	Running Achievable RMSE
Selection Order
0	No Variable	0.00	1.51e+01
1	Froude Number	0.98	1.90
2	Beam-Draught Ratio	0.99	1.46
3	Longitudinal Position	0.99	1.46
4	Length-Displacement	0.99	1.46
5	Prismatic Coeefficient	0.99	1.46
6	Length-Beam Ratio	0.99	1.46