I developed a model in Python, using sklearn, to apply machine learning algorithms with a classified dataset. I applied, for example, the RandomForestClassifier algorithm. I got the values for accuracy, precision, recall, among others. Now, I want to put this model into production. I want to send a record to the model and receive the ..
I have some data in .txt and an instance formed by two lines which both have 100 elements in them. First line defines the problem and the second line defines the solution. Even though it is not a great idea I tried to use a supervised setting among the data. However, I am facing problems ..
I am trying to use an input dataset in the form of a MS Excel (can be any format) to predict an output in the excel(same as input) format using supervised learning. In order to create the training/testing set, I have a large amount of data, yet I dont know how to use an entire ..
I know that scikit-learn provides for roc_auc_score function to calculate roc-auc score metric, including for multiclass classification. However, this function can only be used with classifiers that support the predict_proba probability estimate methods such as decision trees. When using a classifier that does not provide that method, such as Perceptron for example, one has to ..
I have some medical report and I want to classify the text inside, for now, I want to classify the date, the doctor name, the patient name with supervised machine learning. Since the documents I have are medical report there is no real sentences so I think I will probably use bounding boxes and maybe ..
Hi I have a base with p=40 and n=11750, I want to build a model with Ridge classifier (because the objective is predictive if one person is going to be defaulter=0 o not defaulter=1) that select the 10 most representative features in a 10-fold Cross Validation and then calculate de accuracy of the model. For ..
The dataset contains Serial numbers which are alphanumeric of out that, I need to find 4 digit code for the given number. please help me to find the model or any technique to find pattern behind I have data of around 200rows. dataset Source: Python..
I have a TimeSeries dataset which has plots like the one showed below. I am trying to find the best way to do segmentation of the time series. I need the time series divided into three regions – ‘RampUp’, ‘Plateua’ and ‘CoolDown’ for the initial slope up part, the approximately constant part and the final ..
I am trying to visualize the decision boundary for a classification task. While i’ve read some good paper here (Plot k-Nearest-Neighbor graph with 8 features?) and here (https://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/tutorial/plot_knn_iris.html) i encounter an error: MemoryError: Unable to allocate 737. GiB for an array with shape (98903372450,) and data type float64 Can i reduce my sample or sth ..
I am during the reading of very ineteresting short article on the LASSO simulation. Neverthless I do not understand what the plot shows us in the end. I read the code but still dont really know. Can you please help? Here is the article Source: Python-3x..