我是学习者。我正在研究互联网上的“人类活动识别”数据集。它有563个变量,最后一个变量是必须预测的类变量“Activity”。
我试图从CAR的CARET包中使用KNN算法。
我创建了另一个数据集,其中包含561个数字变量,不包括最后一个 - 主题和活动。
我在那里运行了PCA,并决定使用前20台个人电脑。
pca1 <- prcomp(human2, scale = TRUE)
我将这些PC的数据保存在另一个名为'newdat'的数据集中
newdat <- pca1$x[ ,1:20]
现在我试图运行下面的代码:但它给了我错误,因为,这个newday没有我的类变量
trctrl <- trainControl(method = "repeatedcv", number = 10, repeats = 3)
set.seed(3333)
knn_fit <- train(Activity ~., data = newdat, method = "knn",
trControl=trctrl,
preProcess = c("center", "scale"),
tuneLength = 10)
我试图从原始数据中提取最后一列“活动”,并使用带有'newdat'的cbind()将其附加到knn-fit(上面)但是没有附加。
有关如何使用PC的任何建议?
以下是代码:
human1 <- read.csv("C:/NIIT/Term 2/Prog for Analytics II/human-activity-recognition-with-smartphones (1)/train1.csv", header = TRUE)
humant <- read.csv("C:/NIIT/Term 2/Prog for Analytics II/human-activity-recognition-with-smartphones (1)/test1.csv", header = TRUE)
#taking the predictor columns
human2 <- human1[ ,1:561]
pca1 <- prcomp(human2, scale = TRUE)
newdat <- pca1$x[ ,1:15]
newdat <- cbind(newdat, Activity = as.character(human1$Activity))
pca1 <- preProcess(human1[,1:561],
method=c("BoxCox", "center",
"scale", "pca"))
PC = predict(pca1, human1[,1:561])
trctrl <- trainControl(method = "repeatedcv", number = 10, repeats = 3)
set.seed(3333)
knn_fit <- train(Activity ~., data = newdat, method = "knn",
trControl=trctrl,
preProcess = c("center", "scale"),
tuneLength = 10)
#applying knn_fit to test data
test_pred <- predict(knn_fit, newdata = testing)
test_pred
#checking the prediction
confusionMatrix(test_pred, testing$V1 )
我在下面的部分遇到了错误。我附上了错误:
> knn_fit <- train(Activity ~., data = newdat, method = "knn",
+ trControl=trctrl,
+ preProcess = c("center", "scale"),
+ tuneLength = 10)
Error: cannot allocate vector of size 1.3 Gb
您是如何尝试cbind列的,请您显示代码?我想你只是介入了StringsAsFactors = TRUE
产生的困难。以下行是否解决了您的问题:
#...
#newdat <- pca1$x[ ,1:20]
newdat <- cbind(newdat, Activity = as.character(human2$Activity))