Getting error: ufunc 'subtract' did not contain a loop with signature matching types dtype('<U32') dtype('<U32') dtype('<U32')

Question

I'm getting the error I stated in the title on my machine learning project. I'm following a guide on the internet . here's the parts that I'm getting the error:

def euclideanDistance(instance1, instance2, length):
    distance = 0
    for x in range(length):
        distance += pow((instance1[x] - instance2[x]), 2)
    return math.sqrt(distance)

def getNeighbors(trainingSet, testInstance, k):
    distances = []
    length = len(testInstance)-1
    for x in range(len(trainingSet)):
        dist = euclideanDistance(testInstance, trainingSet[x], length)
        distances.append((trainingSet[x], dist))
    distances.sort(key=operator.itemgetter(1))
    neighbors = []
    for x in range(k):
        neighbors.append(distances[x][0])
    return neighbors

neighbors = getNeighbors(training_feature_list, test_feature_list, 3)
print(neighbors)

I've looked around the internet about this question and noticed that many people asked this before but as I understand, the problem emerges from trying to use ufunc on different types of variables. But my training_feature_list and test_feature_list are similar.

train set goes like [['5.1' '0.2']['4.9' '0.2']...(30 rows)

test set goes like [['4.8' '0.2']['5.4' '0.4']...(20 rows).

I'd be so glad if anyone could briefly explain why this problem emerges (because I probably didn't understand it well) and how to fix it.

thanks in advance

Answer 1

If your lists really look like [['5.1' '0.2']['4.9' '0.2']... , then the error is probably caused by the fact that you are trying to subtract one string from another as '5.1' is a string, while 5.1 (which you prbably want) is a floating point number.

If that is not the case than another possible cause for the error (although I would expect a different one) is that you are passing lists instead of numpy arrays, which you should preferably do for calculations, as you can not just subtract one list from another.