There are several ways to transform this variable. In the picture I see, that there are not only bins, but also value ’55+’, it needs to be considered. 1) One liner: df[‘age’].apply(lambda x: np.mean([int(x.split(‘-‘)[0]), int(x.split(‘-‘)[1])]) if ‘+’ not in x else x[:-1]) It checks whether the value contains ‘+’ (like 55+), if yes than the … Read more
Yes..you can get a good accuracy in the first epoch as well. It depends more on the complexity of the data and the model you build. sometimes if the learning rate is too high, than also it could so happen you get a higher training accuracy. Also, coming to the adjusting weights and biases part, … Read more
First of all, there seems to be a mistake in your code. Both if and else conditions set your mat1[i,j] to 1… Supposing your code is actually: for i in range(0,4): for j in range(0,4): if edges[i,j]==1 or (edges[i,0]==1 and edges[0,j]==1): mat1[i,j]=1 Then a Tensorflow solution is: import tensorflow as tf edges = tf.constant([[0, 0, … Read more
The error is in above line. You forgot to close the brackets there. Change this: print(clf.predict(x_test[1:10]) to print(clf.predict(x_test[1:10])) And even after that you will get error in the line: clf.f1_score(…) The above line is wrong, it should be: f1_score(y_test, clf.predict(x_test)) solved Scikit-learn Custom Scoring Function 1
You can use a CNN: The input is then not 3 * w * h but (3*number of images) * w * h – so you can just concatenate the stuff in depth The output is just an image instead of a class. So no flattening in between… or a reshape has to be added. … Read more
Why not learn the numerical representations for each base? This is a common problem in Neural Machine Translation, where we seek to encode “words” with a meaning as (naively) numbers. The core idea is that different words should not be represented with simple numbers, but with a learned dense vector. The process of finding this … Read more
For nicely distributed data, I expect that the most effective way will be to start with a k-means clustering. If each resulting cluster fits within the schools’ capacities, you have a solution. However, your “worry” case is where at least one school is over capacity. For instance, you have 20 children on the north side … Read more
One particular dataset is benchmark for image classification in the computer vision and machine learning literature solved One particular dataset is benchmark for image classification in the computer vision and machine learning literature
It sounds as if you’ve trained to a discrete classification, but you want continuous output. Switch your algorithm to do regression, rather than classification. Another possibility is to harness your last-layer output to interpolate. Use the weights given to the top choice and its strongest adjacent choice. For instance, if your classification gives 1 .01 … Read more
Please check out this site: http://sujitpal.blogspot.com/2008/10/ir-math-in-java-experiments-in.html#ga This would help you out with different algos and you can come up with the best as per your requirements. solved Clustering of sentences [closed]
import itertools import pandas as pd dfs_in_list = [df1, df2, df3, df4, df5] combinations = [] for length in range(2, len(dfs_in_list)): combinations.extend(list(itertools.combinations(dfs_in_list, length))) for c in combinations: pd.concat(c, axis=1) 0 solved Combinations of DataFrames from list
Check these out in that order 🙂 Natural Language Tool Kit [NLTK] main page(It is in Python),Building a machine learning class around NLTK And Making an actual Application out of it. This should give you a great foundation for building NLP applications(provided your NLP fundamentals are strong) solved Machine understand natural language – nlp [closed]