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thingiverse

# It looks like we have some Python code for a support vector machine (SVM) model. Here's how it can be refactored and made more maintainable: ### Data Importing First off, let's clean up the way you're importing your data. ```python import numpy as np ``` Next up is getting that beautiful-looking data in an actual readable format! It looks like a pandas dataframe will make this easier. ```python import pandas as pd # Assuming support_vectors, targets and n_iter are variables, import the appropriate file here... # Here we assume you've loaded your support vector coefficients, classes and number of iterations from some kind of data source. Let's assign them some reasonable variable names for now. n_classes, support_vector_coefficients = len(np.unique(targets)), support_vector_coefficients n_samples, n_features = targets.shape data_points = pd.DataFrame({'Point': targets, 'X1':support_vectors[:,0],'Y1': support_vectors[:, 1]}) ``` Let me know what kind of data source you're reading from, so I can tailor the import to that!