[bug report] cubist difference between predict and tidypredict_to_column

[jacekkotowski]

data(BostonHousing)
BostonHousing$chas <- as.numeric(BostonHousing$chas) - 1

set.seed(1)
inTrain <- sample(1:nrow(BostonHousing), floor(.8*nrow(BostonHousing)))

train_pred <- BostonHousing[ inTrain, -14]
test_pred <- BostonHousing[-inTrain, -14]

train_resp <- BostonHousing$medv[ inTrain]
test_resp <- BostonHousing$medv[-inTrain]

com_model <- cubist(x = train_pred, y = train_resp, committees = 5)

train_cub <- predict(com_model, newdata = train_pred)

predictingFn <- tidypredict_fit(com_model)

#-------------------------
Results

crim	zn	indus	chas	nox	rm	age	dis	rad	tax	ptratio	b	lstat	**real	pred_r	tidypredict**
0,1415	0	6,91	0	0,448	6,169	6,6	5,7209	3	233	17,9	383,37	5,81	**25,3	24,05105	48,158556**
0,09164	0	10,81	0	0,413	6,065	7,8	5,2873	4	305	19,2	390,91	5,52	**22,8	24,00242	42,4043666**
1,42502	0	19,58	0	0,871	6,51	100	1,7659	5	403	14,7	364,31	7,39	**23,3	22,91912	38,14306904**
11,8123	0	18,1	0	0,718	6,824	76,5	1,794	24	666	20,2	48,45	22,74	**8,4	11,54379	19,119236**
10,8342	0	18,1	0	0,679	6,782	90,8	1,8195	24	666	20,2	21,57	25,79	**7,5	10,2055	16,8894594**
14,2362	0	18,1	0	0,693	6,343	100	1,5741	24	666	20,2	396,9	20,32	**7,2	10,98567	17,4945624**
15,8744	0	18,1	0	0,671	6,545	99,1	1,5192	24	666	20,2	396,9	21,08	**10,9	11,43178	16,3770992**
2,77974	0	19,58	0	0,871	4,903	97,8	1,3459	5	403	14,7	396,9	29,29	**11,8	12,31011	17,63297084**

[topepo]

Related to #57 and perhaps #58