Nothing
Code
prep(rec)
Condition
Warning:
Column `x` returned NaN. Consider using `step_zv()` to remove variables containing only a single value.
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 1
-- Training information
Training data contained 10 data points and no incomplete rows.
-- Operations
* Range scaling to [0,1] for: x | Trained
Code
prep(rec)
Condition
Warning:
Column `x` returned NaN. Consider avoiding `Inf` values before normalising.
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 1
-- Training information
Training data contained 4 data points and no incomplete rows.
-- Operations
* Range scaling to [0,1] for: x | Trained
Code
prep(rec)
Condition
Warning:
Column `x` returned NaN. Consider avoiding `Inf` values before normalising.
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 1
-- Training information
Training data contained 4 data points and no incomplete rows.
-- Operations
* Range scaling to [0,1] for: x | Trained
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Range scaling to [0,1] for: <none>
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Training information
Training data contained 32 data points and no incomplete rows.
-- Operations
* Range scaling to [0,1] for: <none> | Trained
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Range scaling to [0,1] for: disp and wt
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Training information
Training data contained 32 data points and no incomplete rows.
-- Operations
* Range scaling to [0,1] for: disp and wt | Trained
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