[ad_1] f = open(‘sample_text.txt’, ‘r’) data = f.read() paragraphs = data.split(“\n\n”) paragraphs[:] = (value for value in paragraphs if value != ‘\t’) 2 [ad_2] solved How can I procees the below text file for text classification? I would like each paragraph as a row in a pandas dataframe, I am unable to do that [closed]
Introduction [ad_1] Text classification is a process of categorizing text into different classes or categories. It is a supervised learning technique that can be used to classify text into different categories such as sentiment analysis, topic classification, spam detection, etc. In this article, we will discuss how to process a text file for text classification … Read more
[ad_1] You can implement a simple linear SVM with numpy only like below. BTW, please google before you ask question next time. There are lots of resources and tutorial online. import numpy as np def my_svm(dataset, label): rate = 1 # rate for gradient descent epochs = 10000 # no of iterations weights = np.zeros(dataset.shape[1]) … Read more
[ad_1] I think u need to do regression analysis to identify the effect of climate on epidemic spread rate. [ad_2] solved What algorithm should be used to extract patterns from datasets?
[ad_1] It subsets the train dataset to only observations where label = 1. 3 [ad_2] solved Can someone explain the following snippet of R code? [closed]
[ad_1] This does not sound like a clustering problem to me. Instead, you are looking for a decision tree, on the target variable “grade > 4”. 0 [ad_2] solved Best data mining algorithm for detect the profile of students with excellent grades
[ad_1] Here I will help you by providing you the template code that you can use and modify according to your needs. I am only going to do for one algorithm then it is your responsibility to do it for others. import pandas as pd import numpy as np import matplotlib.pyplot as plt # read … Read more
[ad_1] Your question is a bit broad, but i’ll try to answer nonetheless. To imitate a subjects behavior you could use and LSTM network which has an understanding of the state it’s in (in your case the state may include information about how fast and in which direction the dot is going and where the … Read more
[ad_1] As sascha observes, constant initial weights aren’t a solution in general anyway because you have to break symmetry. Better solution for the particular context in which I came across the problem: a random number generator that gives the same sequence regardless of type. dtype = np.float64 # Random number generator that returns the correct … Read more
[ad_1] Okay, if your question is “Can I build this ?”, Then the answer is yes. You could train an SVM model to predict the characters based on it’s properties (There may be other models, check them out!). As for the question “Can I use a file from paint ?”, If you are ready to … Read more
[ad_1] Didnt understand your question, but some ML algorithms are: Linear Regression Logistic Regression Neural Networks Support Vector Machines Desicion Trees K-Nearest Neighbor K-Means Principal Component Analysis And some more…. [ad_2] solved What are some machine learning algorithms [closed]
[ad_1] If you look at the feedforwardnet MATLAB help page there is this example: [x,t] = simplefit_dataset; net = feedforwardnet(10); net = train(net,x,t); view(net) y = net(x); perf = perform(net,y,t) This is almost what you want. The feedforwardnet can take an array of different hidden layer sizes, so we can do: net = feedforwardnet([2 10 … Read more
[ad_1] Given a sentence, how can I generate similar sentences of that particular sentence but not with the same meaning using machine learning? [ad_2] solved Given a sentence, how can I generate similar sentences of that particular sentence but not with the same meaning using machine learning?
[ad_1] First, you must to define exactly your time-space. If you want a daily model you must to use “date” as your variable time. For this case, I think waht you need is a time series forecasting model. Linear Regression is an option but there are more sofisticated and useful models for this case. I … Read more
[ad_1] Suppose you train your random forest classifier on 70% of the data you have, then it will help your classifier to identify useful attributes or features for the random forest classifier from this training data. But there are many hyper parameters e.g. depth of a Random Forest classifier, which affects the performance of RF … Read more