fit {BKT} | R Documentation |
fit bkt model
Description
Fit a BKT (Bayesian Knowledge Tracing) model.
This function fits the BKT model using the provided data and various options, such as
skill filtering, forget model, and parallelization. The function uses the model object
created by bkt()
and fits the data according to the specified parameters.
Usage
fit(
object,
data_path = NULL,
data = NULL,
parallel = FALSE,
seed = NULL,
num_fits = 1,
forgets = FALSE,
fixed = NULL,
model_type = NULL,
...
)
Arguments
object |
A BKT model object. The model to be cross-validated. |
data_path |
Character. The file path to the dataset. This will be used if |
data |
Data frame. The dataset to be used for cross-validation. If |
parallel |
Logical. Indicates whether to use parallel computation.
If set to |
seed |
Numeric. Seed for the random number generator, which ensures reproducibility of results. |
num_fits |
Integer. Number of fit iterations. The best model is selected from the total iterations. |
forgets |
Logical. Whether to include a forgetting factor in the model.
If set to |
fixed |
List. A nested list specifying which parameters to fix for specific skills during
model fitting. Each skill can have certain parameters, such as "guesses" and "slips", set to
|
model_type |
Logical vector. Specifies model variants to use. There are four possible variants: 'multilearn', 'multiprior', 'multipair', and 'multigs'. Each corresponds to a different modeling strategy. |
... |
Other parameters. |
Value
A fitted BKT model object, which can be used for predictions, cross-validation, or parameter analysis.
Examples
model <- bkt(seed = 42, parallel = FALSE, num_fits = 1)
result <- fit(
model,
data_path = "data.csv"
)