Gfyuki

May I know how to modify my Python programming so that can obtain the accuracy vs number of neighbours as refer to the attached image file -

# read in the iris data

from sklearn.datasets import load_iris

iris = load_iris()

# create X (features) and y (response)

X = iris.data

y = iris.target



from sklearn.neighbors import KNeighborsClassifier

knn = KNeighborsClassifier(n_neighbors=[1,2,3,4,5,6,7,8,9], metric='minkowski', p=2)

knn.fit(X, y)

y_pred = knn.predict(X)



from sklearn import metrics

metrics.accuracy_score(y,y_pred)

knn = KNeighborsClassifier(n_neighbors=1)

from sklearn.cross_validation import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=0)



# import Matplotlib (scientific plotting library)

import matplotlib.pyplot as plt



# try K=1 through K=9 and record testing accuracy

k_range = range(1, 9)

# create Python dictionary using  

scores = 



for k in k_range:

         knn = KNeighborsClassifier(n_neighbors=k)

         knn.fit(X_train, y_train)

         y_pred = knn.predict(X_test)

         scores.append(metrics.accuracy_score(y_test, y_pred))



# plot the relationship between K and testing accuracy

# plt.plot(x_axis, y_axis)

plt.plot(k_range, scores)

plt.xlabel('Number of neighbors')

plt.ylabel('Accuracy')

The error message is -

runfile('C:/Users/HSIPL/Desktop/Homework 8 Solution draft.py', wdir='C:/Users/HSIPL/Desktop')

Reloaded modules: __mp_main__

Traceback (most recent call last):



  File "<ipython-input-3-1ba40d3637a3>", line 1, in <module>

    runfile('C:/Users/HSIPL/Desktop/Homework 8 Solution draft.py', wdir='C:/Users/HSIPL/Desktop')



  File "C:UsersHSIPLAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 668, in runfile

    execfile(filename, namespace)



  File "C:UsersHSIPLAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 108, in execfile

    exec(compile(f.read(), filename, 'exec'), namespace)



  File "C:/Users/HSIPL/Desktop/Homework 8 Solution draft.py", line 11, in <module>

    knn.fit(X, y)



  File "C:UsersHSIPLAnaconda3libsite-packagessklearnneighborsbase.py", line 790, in fit

    return self._fit(X)



  File "C:UsersHSIPLAnaconda3libsite-packagessklearnneighborsbase.py", line 229, in _fit

    self.n_neighbors < self._fit_X.shape[0] // 2) and



TypeError: '<' not supported between instances of 'list' and 'int'

Please help me on this case so that I can improve my computing skills

Tip:

Your problem is here:

knn = KNeighborsClassifier(n_neighbors=[1,2,3,4,5,6,7,8,9], metric='minkowski', p=2)

You should always refer to documentation when you are using modules with high level of abstraction.

I think it is important on this phase of your learning process to try a bit harder to read documentation. Also I will give you the answer because it is common even after years of experience to be blindfolded by frustration.

Answer (Only look it after trying for at least 10 minutes with the tip)

If we look at sklearn documentation at sklearn.neighbors.KNeighborsClassifier.html you can see the parameters that the KNeighborsClassifier constructor takes:

n_neighbors : int, optional (default = 5)

Number of neighbors to use by default for kneighbors queries.

So, you should always use a single integer when calling this constructor. when you passed [1,2,3,4,5,6,7,8,9] the constructor did not notice that you passed a invalid parameter, that would happen in languages such as C and C++ that tests the parameters data type on function call.

How to do it then?
Well, you LOOP IT!

for k in neighbors:

    knn = KNeighborsClassifier(n_neighbors=k,metric='minkowski', p=2)

    # <todo> ...

Also, check on this tutorial for further clarification.