Create a Dataset from LibSVM files.
make_libsvm_dataset(
file_names,
num_features,
dtype = NULL,
label_dtype = NULL,
batch_size = 1,
compression_type = "",
buffer_size = NULL,
num_parallel_parser_calls = NULL,
drop_final_batch = FALSE,
prefetch_buffer_size = 0
)
A tf.string
tensor containing one or more filenames.
The number of features.
The type of the output feature tensor. Default to tf.float32
.
The type of the output label tensor. Default to
tf.int64
.
An integer representing the number of records to combine in a single batch, default 1.
A tf.string
scalar evaluating to one of ""
(no
compression), "ZLIB"
, or "GZIP"
.
A tf.int64
scalar denoting the number of bytes to
buffer. A value of 0 results in the default buffering values chosen based
on the compression type.
Number of parallel records to parse in parallel. Defaults to an automatic selection.
Whether the last batch should be dropped in case its
size is smaller than batch_size
; the default behavior is not to drop the
smaller batch.
An integer specifying the number of feature batches to prefetch for performance improvement. Defaults to auto-tune. Set to 0 to disable prefetching.