Neural Network returning training data ratio instead of probability
In case of any neural network if you are trying to solve the classification problem then it should generate probabilities.


If you are trying to solve 2 class classification problem then one can opt for sigmoid or softmax. In the case of sigmoid, your neural network only contains 1 output neuron which generates value probability and if probability greater than equal to 50 then belongs to one class and less than 50 then belongs to another class. e.g.(0.333 0.333 0.333) = (0.80) that means belongs class 1 and (0.666 0.333 0.999) = (0.40) that means belongs class 0
In the case of softmax, the neural network should have an equal number of output neurons to the number of categories. e.g.(0.333 0.333 0.333) = (0.80, 0.12, 0.08) that means belongs class 1 and e.g.(0.333 0.333 0.333) = (0.08, 0.20, 0.72) that means belongs class 3