Regression Fuzzy Rule-based System Learner

Fuzzy rule-based regression learner supporting multiple inference engines such as WM, HYFIS, ANFIS, DENFIS, SBC, and several genetic fuzzy systems. Calls frbs::frbs.learn() from frbs.

Dictionary

This Learner can be instantiated via lrn():

lrn("regr.frbs")

Meta Information

• Task type: “regr”

• Predict Types: “response”

• Feature Types: “integer”, “numeric”

• Required Packages: mlr3, mlr3extralearners, frbs

Parameters

Id	Type	Default	Levels	Range
alpha.heuristic	numeric	1		\([2.22044604925031e-16, \infty)\)
d	numeric	2		\((-\infty, \infty)\)
Dthr	numeric	0.1		\([0, 1]\)
eps.high	numeric	0.5		\([2.22044604925031e-16, \infty)\)
eps.low	numeric	0.15		\([2.22044604925031e-16, \infty)\)
epsilon	numeric	0.9		\([0, 1]\)
max.gen	integer	10		\([1, \infty)\)
max.iter	integer	10		\([1, \infty)\)
max.tune	integer	10		\([1, \infty)\)
method.type	character	WM	WM, SBC, HYFIS, ANFIS, DENFIS, FS.HGD, FIR.DM, GFS.FR.MOGUL, GFS.THRIFT, GFS.LT.RS	-
mode.tuning	character	GLOBAL	GLOBAL, LOCAL	-
num.labels	integer	7		\([1, \infty)\)
persen_cross	numeric	1		\([0, 1]\)
persen_mutant	numeric	1		\([0, 1]\)
popu.size	integer	10		\([1, \infty)\)
r.a	numeric	0.5		\([2.22044604925031e-16, \infty)\)
range.data	untyped	NULL		-
rule.selection	logical	FALSE	TRUE, FALSE	-
step.size	numeric	0.01		\([0, 1]\)
type.defuz	character	WAM	WAM, FIRST.MAX, LAST.MAX, MEAN.MAX, COG	-
type.implication.func	character	ZADEH	DIENES_RESHER, LUKASIEWICZ, ZADEH, GOGUEN, GODEL, SHARP, MIZUMOTO, DUBOIS_PRADE, MIN	-
type.mf	character	GAUSSIAN	TRIANGLE, TRAPEZOID, GAUSSIAN, SIGMOID, BELL	-
type.snorm	character	MAX	MAX, HAMACHER, YAGER, PRODUCT, BOUNDED	-
type.tnorm	character	MIN	MIN, HAMACHER, YAGER, PRODUCT, BOUNDED	-

References

Riza LS, Bergmeir C, Herrera F, Benitez JM (2015). “frbs: Fuzzy Rule-Based Systems for Classification and Regression in R.” Journal of Statistical Software, 65(6), 1–30. http://www.jstatsoft.org/v65/i06/.

See also

• Dictionary of Learners: mlr3::mlr_learners.

• as.data.table(mlr_learners) for a table of available Learners in the running session (depending on the loaded packages).

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/basics.html#learners

• mlr3learners for a selection of recommended learners.

• mlr3cluster for unsupervised clustering learners.

• mlr3pipelines to combine learners with pre- and postprocessing steps.

• mlr3tuning for tuning of hyperparameters, mlr3tuningspaces for established default tuning spaces.

Author

awinterstetter

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrFrbs

Methods

Public methods

• LearnerRegrFrbs$new()

• LearnerRegrFrbs$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$configure()
• mlr3::Learner$encapsulate()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$reset()
• mlr3::Learner$selected_features()
• mlr3::Learner$train()
• mlr3::LearnerRegr$predict_newdata_fast()

---

Method new()

Creates a new instance of this R6 class.

Usage

LearnerRegrFrbs$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrFrbs$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Define the Learner
learner = lrn("regr.frbs")
print(learner)
#> 
#> ── <LearnerRegrFrbs> (regr.frbs): Fuzzy Rule-based System ──────────────────────
#> • Model: -
#> • Parameters: list()
#> • Packages: mlr3, mlr3extralearners, and frbs
#> • Predict Types: [response]
#> • Feature Types: integer and numeric
#> • Encapsulation: none (fallback: -)
#> • Properties:
#> • Other settings: use_weights = 'error'

# Define a Task
task = tsk("mtcars")

# Create train and test set
ids = partition(task)

# Train the learner on the training ids
learner$train(task, row_ids = ids$train)

print(learner$model)
#> $num.labels
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#> [1,]    7    7    7    7    7    7    7    7    7     7     7
#> 
#> $varout.mf
#>        vv.small    v.small      small     medium      large    v.large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.00000000 0.16666667 0.33333333 0.50000000 0.66666667 0.83333333
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>        vv.large
#> [1,] 5.00000000
#> [2,] 1.00000000
#> [3,] 0.05833333
#> [4,]         NA
#> [5,]         NA
#> 
#> $rule
#>       [,1] [,2] [,3] [,4]       [,5]  [,6]   [,7] [,8]       [,9]  [,10] [,11]
#>  [1,] "IF" "am" "is" "vv.large" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#>  [2,] "IF" "am" "is" "vv.small" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#>  [3,] "IF" "am" "is" "vv.small" "and" "carb" "is" "v.small"  "and" "cyl" "is" 
#>  [4,] "IF" "am" "is" "vv.small" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#>  [5,] "IF" "am" "is" "vv.small" "and" "carb" "is" "small"    "and" "cyl" "is" 
#>  [6,] "IF" "am" "is" "vv.small" "and" "carb" "is" "small"    "and" "cyl" "is" 
#>  [7,] "IF" "am" "is" "vv.small" "and" "carb" "is" "v.small"  "and" "cyl" "is" 
#>  [8,] "IF" "am" "is" "vv.large" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#>  [9,] "IF" "am" "is" "vv.large" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [10,] "IF" "am" "is" "vv.large" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#> [11,] "IF" "am" "is" "vv.large" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [12,] "IF" "am" "is" "vv.large" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [13,] "IF" "am" "is" "vv.small" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [14,] "IF" "am" "is" "vv.small" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [15,] "IF" "am" "is" "vv.small" "and" "carb" "is" "v.small"  "and" "cyl" "is" 
#> [16,] "IF" "am" "is" "vv.large" "and" "carb" "is" "v.small"  "and" "cyl" "is" 
#> [17,] "IF" "am" "is" "vv.large" "and" "carb" "is" "vv.large" "and" "cyl" "is" 
#> [18,] "IF" "am" "is" "vv.large" "and" "carb" "is" "vv.small" "and" "cyl" "is" 
#> [19,] "IF" "am" "is" "vv.small" "and" "carb" "is" "v.small"  "and" "cyl" "is" 
#> [20,] "IF" "am" "is" "vv.small" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#> [21,] "IF" "am" "is" "vv.small" "and" "carb" "is" "medium"   "and" "cyl" "is" 
#>       [,12]      [,13] [,14]  [,15] [,16]      [,17] [,18]  [,19] [,20]     
#>  [1,] "vv.small" "and" "disp" "is"  "vv.small" "and" "drat" "is"  "vv.large"
#>  [2,] "vv.small" "and" "disp" "is"  "v.small"  "and" "drat" "is"  "large"   
#>  [3,] "vv.small" "and" "disp" "is"  "v.small"  "and" "drat" "is"  "v.large" 
#>  [4,] "medium"   "and" "disp" "is"  "small"    "and" "drat" "is"  "vv.small"
#>  [5,] "vv.large" "and" "disp" "is"  "medium"   "and" "drat" "is"  "v.small" 
#>  [6,] "vv.large" "and" "disp" "is"  "medium"   "and" "drat" "is"  "v.small" 
#>  [7,] "vv.small" "and" "disp" "is"  "v.small"  "and" "drat" "is"  "large"   
#>  [8,] "vv.small" "and" "disp" "is"  "vv.small" "and" "drat" "is"  "v.large" 
#>  [9,] "vv.large" "and" "disp" "is"  "large"    "and" "drat" "is"  "vv.large"
#> [10,] "vv.small" "and" "disp" "is"  "vv.small" "and" "drat" "is"  "v.large" 
#> [11,] "medium"   "and" "disp" "is"  "v.small"  "and" "drat" "is"  "v.large" 
#> [12,] "medium"   "and" "disp" "is"  "v.small"  "and" "drat" "is"  "v.large" 
#> [13,] "vv.large" "and" "disp" "is"  "large"    "and" "drat" "is"  "large"   
#> [14,] "medium"   "and" "disp" "is"  "v.small"  "and" "drat" "is"  "v.large" 
#> [15,] "vv.large" "and" "disp" "is"  "v.large"  "and" "drat" "is"  "v.small" 
#> [16,] "vv.small" "and" "disp" "is"  "v.small"  "and" "drat" "is"  "vv.large"
#> [17,] "vv.large" "and" "disp" "is"  "medium"   "and" "drat" "is"  "medium"  
#> [18,] "vv.small" "and" "disp" "is"  "v.small"  "and" "drat" "is"  "large"   
#> [19,] "vv.large" "and" "disp" "is"  "large"    "and" "drat" "is"  "small"   
#> [20,] "vv.large" "and" "disp" "is"  "vv.large" "and" "drat" "is"  "small"   
#> [21,] "vv.large" "and" "disp" "is"  "vv.large" "and" "drat" "is"  "v.small" 
#>       [,21] [,22]  [,23] [,24]      [,25] [,26] [,27] [,28]      [,29] [,30] 
#>  [1,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "vv.small" "and" "qsec"
#>  [2,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "v.small"  "and" "qsec"
#>  [3,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#>  [4,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "v.small"  "and" "qsec"
#>  [5,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "medium"   "and" "qsec"
#>  [6,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "medium"   "and" "qsec"
#>  [7,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "vv.small" "and" "qsec"
#>  [8,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "vv.small" "and" "qsec"
#>  [9,] "and" "gear" "is"  "vv.large" "and" "hp"  "is"  "large"    "and" "qsec"
#> [10,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "vv.small" "and" "qsec"
#> [11,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#> [12,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#> [13,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "large"    "and" "qsec"
#> [14,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#> [15,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "small"    "and" "qsec"
#> [16,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#> [17,] "and" "gear" "is"  "vv.large" "and" "hp"  "is"  "vv.large" "and" "qsec"
#> [18,] "and" "gear" "is"  "medium"   "and" "hp"  "is"  "v.small"  "and" "qsec"
#> [19,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "small"    "and" "qsec"
#> [20,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "large"    "and" "qsec"
#> [21,] "and" "gear" "is"  "vv.small" "and" "hp"  "is"  "medium"   "and" "qsec"
#>       [,31] [,32]      [,33] [,34] [,35] [,36]      [,37] [,38] [,39]
#>  [1,] "is"  "large"    "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [2,] "is"  "large"    "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [3,] "is"  "vv.large" "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [4,] "is"  "large"    "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [5,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#>  [6,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#>  [7,] "is"  "large"    "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [8,] "is"  "large"    "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#>  [9,] "is"  "vv.small" "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [10,] "is"  "medium"   "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#> [11,] "is"  "v.small"  "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [12,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [13,] "is"  "v.small"  "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [14,] "is"  "medium"   "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#> [15,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [16,] "is"  "medium"   "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#> [17,] "is"  "vv.small" "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [18,] "is"  "medium"   "and" "vs"  "is"  "vv.large" "and" "wt"  "is" 
#> [19,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [20,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#> [21,] "is"  "small"    "and" "vs"  "is"  "vv.small" "and" "wt"  "is" 
#>       [,40]      [,41]  [,42] [,43] [,44]     
#>  [1,] "vv.small" "THEN" "mpg" "is"  "vv.large"
#>  [2,] "v.small"  "THEN" "mpg" "is"  "medium"  
#>  [3,] "small"    "THEN" "mpg" "is"  "medium"  
#>  [4,] "medium"   "THEN" "mpg" "is"  "small"   
#>  [5,] "large"    "THEN" "mpg" "is"  "small"   
#>  [6,] "medium"   "THEN" "mpg" "is"  "small"   
#>  [7,] "small"    "THEN" "mpg" "is"  "large"   
#>  [8,] "v.small"  "THEN" "mpg" "is"  "vv.large"
#>  [9,] "small"    "THEN" "mpg" "is"  "v.small" 
#> [10,] "vv.small" "THEN" "mpg" "is"  "large"   
#> [11,] "v.small"  "THEN" "mpg" "is"  "medium"  
#> [12,] "small"    "THEN" "mpg" "is"  "medium"  
#> [13,] "medium"   "THEN" "mpg" "is"  "v.small" 
#> [14,] "medium"   "THEN" "mpg" "is"  "small"   
#> [15,] "medium"   "THEN" "mpg" "is"  "small"   
#> [16,] "small"    "THEN" "mpg" "is"  "medium"  
#> [17,] "medium"   "THEN" "mpg" "is"  "v.small" 
#> [18,] "v.small"  "THEN" "mpg" "is"  "medium"  
#> [19,] "medium"   "THEN" "mpg" "is"  "small"   
#> [20,] "vv.large" "THEN" "mpg" "is"  "v.small" 
#> [21,] "vv.large" "THEN" "mpg" "is"  "vv.small"
#> 
#> $varinp.mf
#>        vv.small    v.small      small     medium      large    v.large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.00000000 0.16666667 0.33333333 0.50000000 0.66666667 0.83333333
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>        vv.large   vv.small    v.small      small     medium      large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 1.00000000 0.00000000 0.16666667 0.33333333 0.50000000 0.66666667
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>         v.large   vv.large   vv.small    v.small      small     medium
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.83333333 1.00000000 0.00000000 0.16666667 0.33333333 0.50000000
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>           large    v.large   vv.large   vv.small    v.small      small
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.66666667 0.83333333 1.00000000 0.00000000 0.16666667 0.33333333
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>          medium      large    v.large   vv.large   vv.small    v.small
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.50000000 0.66666667 0.83333333 1.00000000 0.00000000 0.16666667
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>           small     medium      large    v.large   vv.large   vv.small
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.33333333 0.50000000 0.66666667 0.83333333 1.00000000 0.00000000
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>         v.small      small     medium      large    v.large   vv.large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.16666667 0.33333333 0.50000000 0.66666667 0.83333333 1.00000000
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>        vv.small    v.small      small     medium      large    v.large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.00000000 0.16666667 0.33333333 0.50000000 0.66666667 0.83333333
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>        vv.large   vv.small    v.small      small     medium      large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 1.00000000 0.00000000 0.16666667 0.33333333 0.50000000 0.66666667
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>         v.large   vv.large   vv.small    v.small      small     medium
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.83333333 1.00000000 0.00000000 0.16666667 0.33333333 0.50000000
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>           large    v.large   vv.large   vv.small    v.small      small
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.66666667 0.83333333 1.00000000 0.00000000 0.16666667 0.33333333
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA         NA         NA
#>          medium      large    v.large   vv.large
#> [1,] 5.00000000 5.00000000 5.00000000 5.00000000
#> [2,] 0.50000000 0.66666667 0.83333333 1.00000000
#> [3,] 0.05833333 0.05833333 0.05833333 0.05833333
#> [4,]         NA         NA         NA         NA
#> [5,]         NA         NA         NA         NA
#> 
#> $degree.ante
#>                
#>  [1,] 0.9200763
#>  [2,] 0.7481040
#>  [3,] 0.7348734
#>  [4,] 0.6869344
#>  [5,] 0.5092745
#>  [6,] 0.5092745
#>  [7,] 0.6648505
#>  [8,] 0.4375647
#>  [9,] 0.4544688
#> [10,] 0.4789988
#> [11,] 0.4725141
#> [12,] 0.4725141
#> [13,] 0.4725141
#> [14,] 0.4468445
#> [15,] 0.3851057
#> [16,] 0.4342669
#> [17,] 0.4525169
#> [18,] 0.3913072
#> [19,] 0.3851057
#> [20,] 0.3921187
#> [21,] 0.3817718
#> 
#> $rule.data.num
#>       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#>  [1,]    7    8   15   22   35   39   43   54   63    64    77
#>  [2,]    1    8   15   23   33   36   44   54   63    65    74
#>  [3,]    1    9   15   23   34   39   44   56   63    66    74
#>  [4,]    1    8   18   24   29   36   44   54   63    67    73
#>  [5,]    1   10   21   25   30   36   46   52   57    68    73
#>  [6,]    1   10   21   25   30   36   46   52   57    67    73
#>  [7,]    1    9   15   23   33   39   43   54   63    66    75
#>  [8,]    7    8   15   22   34   39   43   54   63    65    77
#>  [9,]    7   11   21   26   35   42   47   50   57    66    72
#> [10,]    7    8   15   22   34   39   43   53   63    64    75
#> [11,]    7   11   18   23   34   39   44   51   57    65    74
#> [12,]    7   11   18   23   34   39   44   52   57    66    74
#> [13,]    1   11   21   26   33   36   47   51   57    67    72
#> [14,]    1   11   18   23   34   39   44   53   63    67    73
#> [15,]    1    9   21   27   30   36   45   52   57    67    73
#> [16,]    7    9   15   23   35   39   44   53   63    66    74
#> [17,]    7   14   21   25   32   42   49   50   57    67    72
#> [18,]    7    8   15   23   33   39   44   53   63    65    74
#> [19,]    1    9   21   26   31   36   45   52   57    67    73
#> [20,]    1   11   21   28   31   36   47   52   57    70    72
#> [21,]    1   11   21   28   30   36   46   52   57    70    71
#> 
#> $degree.rule
#>                 
#>  [1,] 0.92007635
#>  [2,] 0.74810403
#>  [3,] 0.73487339
#>  [4,] 0.68693443
#>  [5,] 0.59110655
#>  [6,] 0.50927448
#>  [7,] 0.47754758
#>  [8,] 0.45045471
#>  [9,] 0.44313607
#> [10,] 0.33284074
#> [11,] 0.29663650
#> [12,] 0.29663650
#> [13,] 0.24043998
#> [14,] 0.22013182
#> [15,] 0.22013182
#> [16,] 0.13900452
#> [17,] 0.11683327
#> [18,] 0.10632742
#> [19,] 0.05629793
#> [20,] 0.03834348
#> [21,] 0.00000000
#> 
#> $range.data.ori
#>      [,1] [,2] [,3]  [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#> [1,]    0    1    4  71.1 2.76    3   62 14.5    0 1.835  10.4
#> [2,]    1    8    8 472.0 4.22    5  335 22.9    1 5.345  33.9
#> 
#> $type.mf
#> [1] "GAUSSIAN"
#> 
#> $type.tnorm
#> [1] "MIN"
#> 
#> $type.implication.func
#> [1] "ZADEH"
#> 
#> $type.model
#> [1] "MAMDANI"
#> 
#> $type.defuz
#> [1] "WAM"
#> 
#> $type.snorm
#> [1] "MAX"
#> 
#> $method.type
#> [1] "WM"
#> 
#> $name
#> [1] "sim-0"
#> 
#> $colnames.var
#>  [1] "am"   "carb" "cyl"  "disp" "drat" "gear" "hp"   "qsec" "vs"   "wt"  
#> [11] "mpg" 
#> 
#> attr(,"class")
#> [1] "frbs"


# Make predictions for the test rows
predictions = learner$predict(task, row_ids = ids$test)
#> [1] "note: Some of your new data are out of the previously specified range"
#> [1] "note: Some of your new data are out of the previously specified range"
#> [1] "note: Some of your new data are out of the previously specified range"

# Score the predictions
predictions$score()
#> regr.mse 
#> 7.103764