I want to start experimenting with quantum machine learning using Qiskit library, but I have come across an issue. All tutorials I have seen so far like this one import datasets using custom packages.
In this link its
from datasets import * in other one I saw
from qsvm_datasets import *, but I am unable to import any of those datasets (I get ModuleNotFound error). And I dont really understand what kind of preprocessing is being done before fitting QVSM:
sample_Total, training_input, test_input, class_labels = ad_hoc_data( training_size=training_dataset_size, test_size=testing_dataset_size, n=feature_dim, gap=0.3, PLOT_DATA=True ) datapoints, class_to_label = split_dataset_to_data_and_labels(test_input) algo_input = ClassificationInput(training_input, test_input, datapoints)
My goal is to fit my own data into the classifier, so I really want to udnerstand the steps that need to be done before fitting the classifier. Is there any documentation or more detailed tutorial that I could follow?