小编App*_*te0的帖子

我正在尝试使用R中的插入符包调整参数,但得到一个

Error in train.default(x = as.matrix(df_train %>% select(-c(Response,  : 
  The tuning parameter grid should have columns nrounds, lambda, alpha 

每当我尝试训练模型时,即使列nrounds,lambda和alpha都存在.

library(caret)
library(xgboost)
library(readr)
library(dplyr)
library(tidyr)

 xgb_grid_1 <- expand.grid(
  nrounds= 2400,
  eta=c(0.01,0.001,0.0001),
  lambda = 1,
  alpha =0
)

xgb_trcontrol <- trainControl(
  method="cv",
  number = 5,
  verboseIter = TRUE,
  returnData=FALSE,
  returnResamp = "all",
  allowParallel = TRUE,

)

xgb_train_1 <- train(
  x = as.matrix(df_train %>% select(-c(Response, Id))),
  y= df_train$Response,
 trControl = xgb_trcontrol,
 tuneGrid = xgb_grid_1,
 method="xgbLinear"
)

我试图在R中绘制一个C5.0对象树,但它给出了以下错误,我似乎无法找到如何解决它.

plot(model)

Error in partysplit(varid = as.integer(i), index = index, info = k, prob = NULL)   : 
 minimum of ‘index’ is not equal to 1
In addition: Warning message:
In min(index, na.rm = TRUE) :
 no non-missing arguments to min; returning Inf

我试图弄清楚为什么 int8 比 float 数据类型使用更多的内存。不应该更少吗，因为它应该只使用 1 个字节的内存。

import numpy as np
import sys

In [32]: sys.getsizeof(np.int8(29.200))
Out[32]: 25

In [33]: sys.getsizeof(np.int16(29.200))
Out[33]: 26

In [34]: sys.getsizeof(np.int32(29.200))
Out[34]: 28

In [35]: sys.getsizeof(np.float(29.200))
Out[35]: 24

In [36]: sys.getsizeof(np.float32(29.200))
Out[36]: 28

In [37]: sys.getsizeof(np.float64(29.200))
Out[37]: 32