#hashtag-recommender-system v0.1. Copyright © the Dream Team. Distributed under the MIT license.
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Usage: hashtag-recommender-system [OPTIONS]
Recommends appropriate hashtags for a given image.
-b, --batch-size <Batch Size> Number of sample taken after
each iteration of minibatch
kmeans
--centroid-similarity <arg> Minimum cosine similarity
between the sets of centroids
between 2 iterations to stop
the clusterization process.
--closest-images <arg> Number of the most similar
images to consider for
predicting hashtags.
-c, --clustering-method <Clustering Method> Name of the algorythm to use
for clusterizing the dataset,
can be either kmeans or
minibatch
-d, --debug Enables debug output, disabled
by default.
-f, --features-file <Images file> Path to a file containing image
features to be used by the
system for making hashtag
predictions
--image-path <arg> Path to an image to predict
hashtags for. Can be a local
path or a remote URL.
--in-cluster-file <arg> File to load the clusterized
dataset from. If provided, the
clustering process won't be
executed.
-i, --iterations <arg> Number of iterations that the
clustering algorythm will be
run for. If 0 other criteria
are used to determine when data
are clasterized enough for the
system.
-k, --k <clusters> Number of clusters to create.
If 0 or not provided a
heuristic approach is used to
estimate the optimal value
-m, --master-u-r-l <Master URL> Master URL
-o, --out-cluster-file <arg> Path to a file where the
clusterized dataset will be
saved to.
-r, --rss-variation <RSS Variation> RSS (Residual Sum of Squares)
minimum variation between 2
iterations to stop the process
of clustering.
-s, --ssi Calculates the SSI (Silhouett
Score Index) after clusterizing
the dataset. Warning: computing
the SSI slows down *a lot* the
program execution.
-t, --tag-file <Hashtag file> Path to a file containing a
list of the hashtags that the
system will be able to predict
-h, --help Show help message
-v, --version Show version of this program