image of dataset I want to delete all the data corresponding to total cloud coverage =-1% and also I have to consider the values of total cloud coverage at an interval of 10. Can someone suggest a code that might help for this Source: Python..
I am trying to play around with stuff from a research paper (https://arxiv.org/pdf/2108.13952.pdf). As part of this, they: train a base model generate n student models from this base model by changing the weights It is my expectation and confirmed in the paper that the base and student models will differ in their perfomrance because ..
I’m perfoming a LinearRegression model with a pipeline and GridSearchCV, i can not manege to make it to the coefficients that are calculated for each feature of X_train. mlr_gridsearchcv = Pipeline(steps =[(‘preprocessor’, preprocessor), (‘gridsearchcv_lr’, GridSearchCV(TransformedTargetRegressor(regressor= LinearRegression(), func = np.log,inverse_func = np.exp), param_grid=parameter_lr, cv = nfolds, scoring = (‘r2′,’neg_mean_absolute_error’), return_train_score = True, refit=’neg_mean_absolute_error’, n_jobs = -1))]) ..
Is it bad practice to run a Machine learning algorithm on an experimental dataset, check the MAE, and remove the instances that have a value of MAE above a certain value? If we run the algorithm without those instances the accuracy increases significantly of course. I know that something similar can be used when we ..
I am quite new to ML and signal processing and wanted to ask for help with validating my RF model. I am analysing acoustic data in search for a particular signal. Labelled data and run the code to get RF algorithm: data = pd.read_csv(‘C:/Users/m/Desktop/nilesh_cooper/coding/test_data/features.csv’, index_col=0) from sklearn.model_selection import train_test_split #setting features and labels datasets within ..
I am trying to carry out OCR on simple handwritten texts I have extracted from a document. However, I am not getting very good results using tesseract. Can anyone suggest some pre-trained ML/DL model for extracting text content from the files present here: sample images or, alternatively if they have a way to do it ..
Hi I’m trying to create a program that show top 3 of similar image to query image, using python. I thought Siamese Network by Triplet Loss can be good option for what I want to do. I wrote some codes and created model with small dataset in my pc. And I inputted one of the ..
I have a simple NN: import torch import torch.nn as nn import torch.optim as optim class Model(nn.Module): def __init__(self): super(Model, self).__init__() self.fc1 = nn.Linear(1, 5) self.fc2 = nn.Linear(5, 10) self.fc3 = nn.Linear(10, 1) def forward(self, x): x = self.fc1(x) x = torch.relu(x) x = torch.relu(self.fc2(x)) x = self.fc3(x) return x net = Model() opt = ..
I have a task to implement a model based on graph neural networks to simulate a breadth first search algorithm. I am doing sort of a iterative node prediction so i put the nodes in the BFS queue in sorted manner (lowest edge weights takes precedence) such that the network can learn. (as compared to ..
Here I am trying to find machine learning models deployment solution where I can protect my intellectuals. Create SaaS and deploy on the some cloud but I am not sure client would like to agree to put data out side of there world. Deploy it in client’s environment but there is possibility to expose your ..