Top "Prediction" questions

For questions related to statistical prediction, especially for programming tasks.

Accuracy Score ValueError: Can't Handle mix of binary and continuous target

I'm using linear_model.LinearRegression from scikit-learn as a predictive model. It works and it's perfect. I have a problem …

python machine-learning scikit-learn linear-regression prediction
ValueError: Wrong number of items passed - Meaning and suggestions?

I am receiving the error: ValueError: Wrong number of items passed 3, placement implies 1, and I am struggling to figure out …

python pandas prediction data-science
Error in eval(predvars, data, env) : object 'Rm' not found

dataset = read.csv('dataset/housing.header.binary.txt') dataset1 = dataset[6] #higest positive correlation dataset2 = dataset[13] #lowest negative correlation dependentVal= dataset[14] #…

r classification prediction rpart
Getting Warning: " 'newdata' had 1 row but variables found have 32 rows" on predict.lm

I found peculiarity while using predict and lm function in R. I got different results for data frame and vector …

r prediction lm
R: how to make a confusion matrix for a predictive model?

I have a dataframe. first column contains my the predictive score (range from 0 to 100, smaller values is expected to be …

r prediction
Is it possible to predict the next number in a number generator?

With programming, it is never "random". Even the random generator uses an algorithm to predict a random number. But, if …

random prediction
Predicting missing values with scikit-learn's Imputer module

I am writing a very basic program to predict missing values in a dataset using scikit-learn's Imputer class. I have …

python numpy scikit-learn prediction imputation
Working with neuralnet in R for the first time: get "requires numeric/complex matrix/vector arguments"

I'm in the process of attempting to learn to work with neural networks in R. As a learning problem, I've …

r regression prediction kaggle
Error in terms.formula(formula) : '.' in formula and no 'data' argument

I'm tring to use neuralnet for prediction. Create some X: x <- cbind(seq(1, 50, 1), seq(51, 100, 1)) Create Y: y <…

r formula prediction
How does predict.lm() compute confidence interval and prediction interval?

I ran a regression: CopierDataRegression <- lm(V1~V2, data=CopierData1) and my task was to obtain a 90% confidence …

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