Predict method for class `big_sp_list`

.

# S3 method for big_sp_list
predict(
object,
X,
ind.row = rows_along(X),
ind.col = attr(object, "ind.col"),
covar.row = NULL,
proba = (attr(object, "family") == "binomial"),
base.row = NULL,
ncores = 1,
...
)

## Arguments

object |
Object of class `big_sp_list` . |

X |
An object of class FBM. |

ind.row |
An optional vector of the row indices that are used.
If not specified, all rows are used. **Don't use negative indices.** |

ind.col |
An optional vector of the column indices that are used.
If not specified, all columns are used. **Don't use negative indices.** |

covar.row |
Matrix of covariables to be added in each model to correct
for confounders (e.g. the scores of PCA), corresponding to `ind.row` .
Default is `NULL` and corresponds to only adding an intercept to each model.
You can use `covar_from_df()` to convert from a data frame. |

proba |
Whether to return probabilities? |

base.row |
Vector of base predictions, corresponding to `ind.row` . |

ncores |
Number of cores used. Default doesn't use parallelism.
You may use nb_cores. |

... |
Not used. |

## Value

A vector of scores, corresponding to `ind.row`

.

## See also