prediction
AttributeError: ‘Model’ object has no attribute ‘predict_classes’
The predict_classes method is only available for the Sequential class (which is the class of your first model) but not for the Model class (the class of your second model). With the Model class, you can use the predict method which will give you a vector of probabilities and then get the argmax of this … Read more
Extract prediction band from lme fit
Warning: Read this thread on r-sig-mixed models before doing this. Be very careful when you interpret the resulting prediction band. From r-sig-mixed models FAQ adjusted to your example: set.seed(42) x <- rep(0:100,10) y <- 15 + 2*rnorm(1010,10,4)*x + rnorm(1010,20,100) id<-rep(1:10,each=101) dtfr <- data.frame(x=x ,y=y, id=id) library(nlme) model.mx <- lme(y~x,random=~1+x|id,data=dtfr) #create data.frame with new values for … Read more
ValueError: Wrong number of items passed – Meaning and suggestions?
In general, the error ValueError: Wrong number of items passed 3, placement implies 1 suggests that you are attempting to put too many pigeons in too few pigeonholes. In this case, the value on the right of the equation results[‘predictedY’] = predictedY is trying to put 3 “things” into a container that allows only one. … Read more
Keep same dummy variable in training and testing data
You can also just get the missing columns and add them to the test dataset: # Get missing columns in the training test missing_cols = set( train.columns ) – set( test.columns ) # Add a missing column in test set with default value equal to 0 for c in missing_cols: test[c] = 0 # Ensure … Read more
Accuracy Score ValueError: Can’t Handle mix of binary and continuous target
Despite the plethora of wrong answers here that attempt to circumvent the error by numerically manipulating the predictions, the root cause of your error is a theoretical and not computational issue: you are trying to use a classification metric (accuracy) in a regression (i.e. numeric prediction) model (LinearRegression), which is meaningless. Just like the majority … Read more
How does predict.lm() compute confidence interval and prediction interval?
When specifying interval and level argument, predict.lm can return confidence interval (CI) or prediction interval (PI). This answer shows how to obtain CI and PI without setting these arguments. There are two ways: use middle-stage result from predict.lm; do everything from scratch. Knowing how to work with both ways give you a thorough understand of … Read more
Getting Warning: ” ‘newdata’ had 1 row but variables found have 32 rows” on predict.lm
This is a problem of using different names between your data and your newdata and not a problem between using vectors or dataframes. When you fit a model with the lm function and then use predict to make predictions, predict tries to find the same names on your newdata. In your first case name x … Read more