ValueError: Found input variables with inconsistent numbers of sample [100, 300]

I am new to Python and I am trying to complete a piece of coursework that involves Support Vector Machines, Principal Component Analysis and Cost-Support Vector Classifiers.

Firstly I have made a scatter plot from two sets of data that were provided.

I have normalised the data and believed i have split the data into smaller datasets using train_test_spilt.

The issue occurs when I am using the C-SVC SVM to achieve the highest classification rate of the data I have collected from the scatter plot, by imputing two values in the parameters C(cost) and γ(gamma). The code is as follows:

svc1 = SVC(kernel ='rbf', class_weight='balanced', C=50, gamma=0.1)
model1 = svc1.fit(scaled_tester, Sytrain)

"""The fitted model should be validated on the scaled validation set. """
vyfit1 = model1.predict(scaled_valX)

"""Performance measurements"""
from sklearn import metrics 
print('Accuracy:', metrics.accuracy_score(vtest, vyfit1))

from sklearn.metrics import classification_report
print(classification_report(vtest, vyfit1,
                            target_names=faces.target_names))

The error message is as follows:

Error:
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-82-9a74f54d417b> in <module>
      1 svc1 = SVC(kernel ='rbf', class_weight='balanced', C=50, gamma=0.1)
----> 2 model1 = svc1.fit(scaled_tester, Sytrain)
      3 
      4 """The fitted model should be validated on the scaled validation set. """
      5 vyfit1 = model1.predict(scaled_valX)

/opt/anaconda3/lib/python3.7/site-packages/sklearn/svm/_base.py in fit(self, X, y, sample_weight)
    146         X, y = check_X_y(X, y, dtype=np.float64,
    147                          order='C', accept_sparse='csr',
--> 148                          accept_large_sparse=False)
    149         y = self._validate_targets(y)
    150 

/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)
    763         y = y.astype(np.float64)
    764 
--> 765     check_consistent_length(X, y)
    766 
    767     return X, y

/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in check_consistent_length(*arrays)
    210     if len(uniques) > 1:
    211         raise ValueError("Found input variables with inconsistent numbers of"
--> 212                          " samples: %r" % [int(l) for l in lengths])
    213 
    214 

ValueError: Found input variables with inconsistent numbers of samples: [100, 300]

Is there anyone who is able to understand this error message and tell me where it is going wrong?

Many Thanks any questions please let me know.