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H: Group neural networks outputs using Keras/Tensorflow I am trying to group the outputs of my neural network, in order to have them perform a separated classification. Let's take the example where the groups are constituted of two nodes and we previously have four output nodes, then the network should look like this ...
H: Is my model overfitting? The validation loss keeps on fluctuating I have trained a 4 layer neural network model = Sequential() #get number of columns in training data n_cols = X_train.shape[1] #add model layers model.add(Dense(8, activation='relu', input_shape=(n_cols,))) model.add(Dense(8, activation='relu')) mo...
H: Why my svm.SVC.fit( ) (linear kernal) run so long time? I am using sklearn.svm.SVC( ) to train & test my dataset. 80% are used for training, 20% are used for testing. Here is my Python code: data = pd.read_csv(trainPath, header=0) X = data.iloc[:, 5:17].values y = data.iloc[:, 17:18].values X_train, X_test, y_tra...
H: Why is data science not yet widely applied to Law? Law (judiciary) contains such a huge corpus to apply NLP to, but yet there are only search engines designed for Law. Why is NLP not yet extensively applied? Is it because of dimensionality? AI: Welcome to the site and thanks for the great question! I recently led a...
H: Gradient Boosted Decision Trees How to Find Prediction of Each Tree? I'm doing a project. I have a classification problem that I should solve using gradient boosted decision trees. What I want to do is create a matrix that gives prediction of each decision tree for each sample. For example if I have 100 samples and...
H: Resampling for imbalaced datasets: should testing set also be resampled? Apologies for what is probably a basic question but I have not been able to find a definitive answer either in the literature or in the Internet. When dealing with an imbalanced dataset one possible strategy is to resample either the minority...
H: Oversampling only balances the training set, what about the testing set? In a case of imbalanced data classification, I know that we only oversample the training set (to prevent data leakage from training to testing subsets), but what if there are no positive data points in my testing set? The testing set is still ...
H: Why is my Python Altair chart printing a blank line? Wondering if anyone can help me understand why python altair chart is not printing... I’m only seeing this when I run the code: It literally isn’t outputting anything. This is what my chart looks like converted to_dict; recommended for troubleshooting to ensure ...
H: What are the factors to consider when setting the depth of a decision tree? In scikit learn, one of the parameters to set when instantiating a decision tree is the maximum depth. What are the factors to consider when setting the depth of a decision tree? Does larger depth usually lead to higher accuracy? AI: Yes, b...
H: How will a decision tree cope if it cannot find a suitable feature to choose as root node from which to split further? When I look at decision trees, they start with a root node choosing the most suitable feature from which to split further. What if the decision tree is unable to find the most suitable feature from...
H: Why are bigger embedding vectors not necessarily better? I'm wondering why increasing the dimension of a word dimension vector in NLP doesn't necessarily lead to a better result. For instance, on examples I run, I see sometimes that using a pre-trained 100d GloVe vector performs better than a 300d one. Why is this ...
H: Difference between sklearn make_pipeline and imblearn make_pipeline Can anybody please explain the difference between sklearn.pipeline.make_pipline and imblearn.pipeline.make_pipline. AI: The imblearn package contains a lot of different samplers for easy over- or under-sampling of data. These samplers can not be pl...
H: sklearn.model_selection: GridSearchCV vs. KFold Here is the explain of cv parameter in the sklearn.model_selection.GridSearchCV: cv : int, cross-validation generator or an iterable, optional Determines the cross-validation splitting strategy. Possible inputs for cv are: integer, to specify the number of folds in...
H: Track underlying observation when using GridSearchCV and make_scorer I'm doing a GridSearchCV, and I've defined a custom function (called custom_scorer below) to optimize for. So the setup is like this: gs = GridSearchCV(estimator=some_classifier, param_grid=some_grid, cv=5, # ...
H: What is the purpose of standardization in machine learning? I'm just getting started with learning about K-nearest neighbor and am having a hard time understanding why standardization is required. Reading through, I came across a section saying When independent variables in training data are measured in different ...
H: How to extract trees in XGBoost? I want to extract each tree so that I can feed it with any data, and see the output. dump_list=xg_clas.get_booster().get_dump() num_t=len(dump_list) print("Number of Trees=",num_t) I can find number of trees like this, xgb.plot_tree(xg_clas, num_trees=0) plt.rcParams['figure.figsiz...
H: What's a good book (or other resource) to learn Imitation Learning? I must learn and apply imitation learning on a robot for my thesis. I'm looking for decent sources of information on this topic. AI: I found a great book, it's just what I was looking for. In case someone finds it useful: An Algorithmic Perspective...
H: Fit to a power law I often encounter data which I hypothesize to be from a shifted power law, $ y(x) = A x^k + B$. I have in mind samples from an unknown deterministic function here, but you can think about a probability distribution if you prefer. What is the best way to fit such data using Python? The shift means...
H: is gradient descent also used during feed forward propagation in Neural Network? To the best of my understanding , weights are updated during back propagation only using gradient descent and no gradient descent is used during feed forward propagation. is it correct ? AI: The feed-forward pass computes the outputs o...
H: Suggestions for Matchmaking Algorithm I run a heterosexual matching making service. I have my male clients and my female clients. I need to pair each of my clients with their "soul mate" based on several attributes (age, interests, personality types, race, height,horoscope, etc.) After I create all my pairings, t...
H: can we make a word2vec NN of more than 3 layers using tensorflow? To the best of my understanding , word2vec crated using gensim is of 3 layers only. I was wondering can we customize word2vec NN and create word2vec NN of more than 3 layers to experiment with it using tensorflow ? AI: Technically, any Word2vec is ba...
H: Populate free space between two dates I'm new to data science. I'm trying to increase the time-series length for a special calculation. In the original time-series I have 20 weekly reports and I want to increase the amount of occurrences to 200. Is it ok just to use the range from the first date value to second dat...
H: What do I need to learn in order to really understand Machine Learning? I've graduated with a math major in undergrad, but mostly focused on algebra (Galois Theory, Knot theory, etc.). I work in something unrelated right now, but now I want to study machine learning. The question is, what kind of knowledge should I...
H: GPS generate street I am working on GPS tracking with a huge data from vehicle. Dataset have: vehicleId, speed, orientation(0-360), coordinate (x,y) and timestamp. Can you recommend me how to clean data and model to generate street(route) from data? just 1000 GPS. I have about 500k GPS Thank you so much AI: If you...
H: Appraise the statement: “For the model = 0 + 1 + , 1 reflects the causal effect of on .” Ask not sure if this was the right place to ask my question, but I saw some questions regarding linear regression so I'd thought I would try to get some answers here. I just started learning about linear regression so this is...
H: What are the best practises to decide whether a variable is categorical? What are some of the systematic ways to categorise variables into categorical or numeric? I believe using only intuition in such scenarios can many-a-times lead to major irreversible errors. What are the best strategies when categorising varia...
H: Logistics regression with polynomial features vs neural networks for classification I am taking Andrew Ng's Coursera class on machine learning. He mentions that training a logistic regression model with polynomial features would be very expensive for certain tasks compared to training a neural network. Why is that ...
H: It seems that the output of sklearn.metrics.pairwise.euclidean_distances is different to the formula on doc The doc of sklearn.metrics.pairwise.euclidean_distances() gives this formula dist(x, y) = sqrt(dot(x, x) - 2 * dot(x, y) + dot(y, y)). Apply this formula to this example X = [[0, 1], [2, 3]] Y = [[1,...
H: Face detection for different poses more robust than MTCNN? I am using the MTCNN model described on machinelearningmastery here: MTCNN ipazc But it won't detect certain orientations, ie. somebody lying on the ground so the top of the head points to the right of the frame and their chin to the left. Thus, I am goin...
H: Extracting tokens from a document: applying Deep Learning or Classification? I have a legal document from Law. That document is 4-pages of evidence from the plaintiff. I want to identify the Dates, Addresses and Financial transactions in that document. Can I apply deep learning, the data with me is very small, on j...
H: Overfitting Question Would you consider that overfitting? AI: No, it's not an example of overfitting! It would be overfitting if valid loss started to increase while training loss was going on to decrease. Edit: the answer for the second question It's worth considering how auc is calculated. We have the probabili...
H: how to handle values that only appear once in a column? Counting the values of a column using pandas I got the following result: Human 195 Mutant 62 God / Eternal 14 Cyborg 11 Human / Radiation 11 Android 9 Symbiote 8 Krypt...
H: Use correlation matrix scores as starting weights and bias inputs for neural network? I have a neural net that's generating an average 15% error across the three outputs it gives. My problem is two of the three really have about a 2% error while the third has around 40%. I was wondering if anyone has used results f...
H: How to find feature importance with multiple XGBoost models My problem statement : Time Series forecasting(Month wise data), training on 96 months of data and predicting next 12 months with a 3 months empty window in between. Example : Batch 1 ***Training Data index*** <2010-01-01 -----------------------------201...
H: Intuition behind the number of output neurons for a neural network I am reading Michael Nielsen's book on deep learning. In the first chapter, he gives the classic example of classifying 10 handwritten digits, and uses it to explain the intuition behind choosing the number of output neurons. Initially, before read...
H: How does an encoder-decoder network work? Let's say I trained an encoder-decoder network on a cat dataset using reconstruction error as loss function. The network is fully trained and the decoder is able to reconstruct good cat images. Now what if I use the same network and input a dog image. Will the network be ab...
H: On design of the training set: conceptual question I am curious to know how training data should be constructed so that it scales to examples that are not a part of the training data. For example, the problem that I am facing right now is in the application of identifying or distinguishing the frequency response of...
H: XGBoost: # rounds is equal to n_estimators? I'm running a regression XGBoost model and trying to prevent over-fitting by watching the train and test error using this code: eval_set = [(X_train, y_train), (X_test, y_test)] xg_reg = xgb.XGBRegressor(booster='gbtree', objective ='reg:squared...
H: forecasting - likelihood of customers participating in next month sales I have historical transaction information of customers for the last 2 years and other information about the customers like what type of card (gold/platinum) they used for transactions etc. is also there in the dataset. Using this dataset, I wil...
H: Conditional Statement to update columns based on range I have a dataframe called clients that has 5000+ rows with the following: ID Ordered Days 1 101565 131 2 202546 122 3 459863 78 4 328453 327 5 458975 -27 I'm trying to create a loop that looks at the numbers of days and r...
H: How to shuffle only a fraction of a column in a Pandas dataframe? I would like to shuffle a fraction (for example 40%) of the values of a specific column in a Pandas dataframe. How would you do it? Is there a simple idiomatic way to do that, maybe using np.random, or sklearn.utils.shuffle? I have searched and only ...
H: Getting a transition matrix from a Adjacency matrix in python I have a 3*3 Adjacency matrix and I'm trying to sum the elements of each column and divide each column element by that sum to get the transition matrix. Can you please help me code this part? Thanks in advance. AI: Considering a is your adjacency matrix ...
H: How does one decide when to use boosting over bagging algorithm? What kind of problem, circumstances and data makes it more suitable to apply boosting instead of bagging methods? AI: Bagging and boosting are two methods of implementing ensemble models. Bagging: each model is given the same inputs as every other and...
H: Is loss the same thing as variance? In Keras, the first object returned in the score list is loss. score = model.evaluate(X_test, y_test,verbose=1) print(score) [1] [0.025217213829228164, 0.99487179487179489] Is this the same thing as variance? AI: No. Loss measures the error between your predicted values and tru...
H: What does high variance mean in a binary classification machine learning model? My understanding of high variance is that the targets are spread widely around. The output values are "all over the place". In a binary classification model, there can only be 2 outcomes. I am at a loss when visualizing what high varia...
H: Error using decision tree regressor I'm new to data science , while i'm implementing decision tree. I'm facing the following error. Where i went wrong; Sample data in csv is: x=dataset.iloc[:,:-1].values y=dataset.iloc[:,:2].values from sklearn.preprocessing import LabelEncoder,OneHotEncoder from sklearn.compose...
H: What is "data scaling" regarding StandardScaler()? I'm trying to figure out the purpose of StandardScaler() in sklearn. The tutorial I am following says "Remember that you also need to perform the scaling again because you had a lot of differences in some of the values for your red and white [wines]" So I looke...
H: normal conda install vs forge install In order to install some libraries, we just use: conda install pandas While in other cases we use: conda install -c conda-forge html5lib What is the difference between them? AI: conda-forge is just an alternative channel where you can upload to or download packages from. Usua...
H: Bagging with Neural Networks Best practices I am trying to build a majority vote system for 3 Neural Networks, and I came across the concept of Bagging method. Actually, I want to use neural networks as weak learners (I know it's debatable, but some papers have tried it and I want to try it too). For more informati...
H: How Linear SVM Regression and Multiple Linear Regression different in terms of the regression result? They starts from the same equation as below. y = w*x + b But they solve it differently. MLR specified the w and b by minimizing the square error whereas SVM specified w and b by minimizing the loss function defined...
H: How to retrieve images from a url in a pandas dataframe and store them as PIL object in a new column I'm trying to store as a PIL object in a new column of a dataframe pictures that are located in a column of the same dataframe in the form of URL's. I've tried the following code: import pandas as pd from PIL import...
H: Using a LinearSVC() for multilabel classification with MultiOutputClassifier() in a pipeline in sci-kit learn My input data is a (23948,) pandas.Series of strings containing newspaper headlines. My target are 20 labels of the headline (e.g. 'crime', 'politics') each binarily encoded with [0, 1]. The labels are not ...
H: How to convert sequence of words in to numbers which are input to RNN/LSTM? I am watching online videos and tutorials about use of RNN/LSTM for NLP but none of them explain how to convert the sequences of words into digitized input to the neural networks? I am looking for intuitive understanding but answers with p...
H: What variance threshold to consider in feature selection? Consider a numerical dataset with continuous variables, that has been scaled to end up with values in the [0,1] range. How can I compute a reasonable variance threshold for all the variables? AI: Usually 3 is taken as a threshold Value by standard deviation ...
H: Extract imperative sentences from a document(English) using NLP in python I am very new to NLP, hence require some help on extracting imperative sentences from a document. I am working on a project where I need to get all the imperative sentences from the entire document(English documents). I understand I need to u...
H: How does the forward method get called in this pyTorch conv net? In this example network from pyTorch tutorial import torch import torch.nn as nn import torch.nn.functional as F class Net(nn.Module): def __init__(self): super(Net, self).__init__() # 1 input image channel, 6 output channels, 3...
H: Layer shape computation in convolutional neural net (pyTorch) How can you know the expected input size (image input size (tensor size)), for example for this network (cf. pyTorch tutorial example ): import torch import torch.nn as nn import torch.nn.functional as F class Net(nn.Module): def __init__(self): ...
H: Subtract Rows of Matrix from rows of another matrix numpy I have two matrix V_r of shape(19, 300) and vecs of shape(100000, 300). I would like to subtract rows of V_r from from rows of vecs. Currently, I am achieving this with the following code. Is there a way to do it using broadcasting? list=[] for v in V_r:...
H: Why my Keras CNN model isn't learning My project have to decide if a image is 'pdr' or 'nonPdr', and I have 391 images (22 of PDR class, and the 369 of nonPdr).. In my first model i was trying this: https://stackoverflow.com/questions/57663233/my-keras-cnn-return-the-same-output-value-how-can-i-fix-improve-my-code ...
H: Sanity check: low PPV but high AUC scores? I have two algorithms running on a piece of data, both of which perform differently. One of them (call it A) consistently gets a positive predictive value of about 0.75-0.78. Looking at the AUC of the Receiver operating characteristic it has a score of about 0.82 The secon...
H: What do we learn from training a dataset for logistic regression What do we learn from training our dataset in Logistic Resgression? Like in Linear Regression, with the help of training set we are able to generate a best fit line(y = mx+c) where m and c come from training our dataset. Similarly, once we train our m...
H: Explained definition of the norm in Ordinary Least Squares I have recently started learning Scikit-learn and I am not able to understand the below equation. Could anybody please explain? AI: The norm indicates the Eucleadan norm, which gives the ordinary distance between the points. https://en.wikipedia.org/wiki/No...
H: Normal distribution and QQ plot I have data that I plotted with a normal distribution and a QQ plot. I was wondering especially in QQ plot it seems that 95.4% of the data is normally distributed. My question is what does numbers meanings that above 2 sigmas in QQ plot? Should remove them or I need to transform this...
H: Are DBSCAN and dbscan from the sklearn.cluster package different? I'm new to DBSCAN. I was looking at a few examples online and came across a few instances where the following lines were used while importing the dbscan module: from sklearn.cluster.dbscan_ import DBSCAN from sklearn.cluster.dbscan_ import dbscan I...
H: How to create dictionaries out of pandas dataframes? I import three csv-files with characteristics of countries (rows) and years (columns): country_data_m = 'country_data_m.csv' m_year = pd.read_csv(country_data_m, nrows=161, index_col=0, header=0, sep=';', na_values=[""]) country_data_e = 'country_data_e.csv' e_y...
H: Interpreting a curve val_loss and loss in keras after training a model I am having trouble understanding the curve val_loss and loss in keras after training my model. Can anyone help me understand it? Also, is my model overfitting or underfitting? AI: The loss curve shows what the model is trying to reduce. The t...
H: Combining 'class_weight' with SMOTE This might sound a weird question, but I could not find enough details in sklearn documentation about 'class_weight'. Can we first oversample the dataset using SMOTE and then call the classifier with the 'class_weight' option? As my testing set is highly imbalanced, I want to pen...
H: Calculate coefficient w* I'm learning ML from Bishop's book. But I don't know that How should I calculate w* in the below picture. AI: Just looked into the book. It was an example of the data that is presented in Fig 1.4. Numpy is a good package to derive the sum of squares fit to the data. This is an optimization ...
H: How to change a Pandas dataframe into feature vector? I have a Pandas dataframe with 10 columns, 9 of which are features to be used to predict the 10th column. How is it ossible to convert this Pandas dataframe into X and y vectors to use in a linear regression problem? AI: If you have your dataframe loaded as the ...
H: How to create correlation matrix but with only part of the rows? I would like to have correlation matrix like this one, but with only 3 bottom rows but all the columns. How can I generate it? corr = corrdata.corr() sns.heatmap(corr, mask=np.zeros_like(corr), annot=True, cmap=sns.diverging_palette(220, 10, as_cmap...
H: How to compare a sentence with a paragraph and get its probability in terms of correctness? This is my first post on stackoverflow network and I am dealing with a machine learning. Lets say I have a paragraph describing a rabbit and tortoise story. The story concludes that tortoise is a winner. Now I want to train ...
H: ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() Firstly I have a pandas series of recommended product (recmd_prdt_list). In this series there is a possibility of presence of deleted products. So as to remove deleted products from the recommended products...
H: Cross validation while preserving a column (not the target ) distribution So i'm doing cross validation and then i'm predicting using all the data on a test set ( a hold-out set ). My hold-out set has the same ratio on a column than the train ( seems thats how the test set was generated, a function that sampled it ...
H: Conditional entropy calculation in python, H(Y|X) Input X: A numpy array whose size gives the number of instances. X contains each instance's attribute value. Y: A numpy array which contains each instance's corresponding target label. Output : Conditional Entropy Can you please help me code the conditional entrop...
H: Which classifier performs better when using 'class_weight'? I have used the 'class_weight' method to balance my multi-class classification problem, using Logistic Regression, Random Forest, and XGBoost classifiers. Among these three methods, logistic regression's performance for the minority classes is substantiall...
H: Can I arbitrarily eliminate 20% of my training data if doing so significantly improves model accuracy? My dataset contains 2000 records with 125 meaningful fields 5 of which are distributed along highly skewed lognormal behavior. I've found that if I eliminate all records below some threshold of this lognormal beha...
H: How to create a parquet file from a query to a mysql table Updating a legacy ~ETL; on it's base it exports some tables of the prod DB to s3, the export contains a query. The export process generates a csv file using the following logic: res = sh.sed( sh.mysql( '-u', settings_dict['USER'], '...
H: General equation for getting an idea of the scale of a machine learning project I'm writing an application for a project where we intend to teach a model to predict one aspect of an environment (traffic safety) using a database with 10 images (about 300x300px and, say, 256 colors) for each of either 100 000 or 15 m...
H: Why models performs better If normalize test data and train data separately? Many threads (and courses) such as this and this one suggest that you should apply normalization to the test data using the parameters used in the training set. But other some discussions I've found like this one and this one that suggest ...
H: My CNN model Accuracy doesn't increase (high loss and low acc) Well, I need to do a CNN to classify if a Image is from one or another class. But my model return high losses (6.~8.) and low accuracies (0.50 on max). I tried to include more layers, change my activation functions, and nothing works. My database is 142...
H: Evaluating pairwise distances between the output of a tf.keras.model I am trying to create a custom loss function in tensorflow. I am using tensorflow v2.0.rc0 for running the code. Following is the code and the function min_dist_loss computes the pairwise loss between the output of the neural network. Here's the c...
H: ValueError: Error when checking input: expected conv2d_1_input to have 4 dimensions, but got array with shape (142, 1) I'm trying to pass all my images (71 for each class) from folder 'train' to model.fit. The method ReadImages get these images and resize them (because are too big 4288x2848).... But when i run my c...
H: Precision Vs Recall Curve analysis I have the following averaged − curves with 4 models. Which one is the best? AI: It depends. The problem you are trying to solve decides which among the curves is the best For example If you are trying to solve a problem that is like identifying cancer where the cost of false pos...
H: How to implement Classification and Anomaly detection (C++) I am creating a system using C++(DX11) and i'm reading raw data into my program, i want to classify what the 3D data-set i'm reading in is and detect any anomalies it may have when compared to a database of the same types of item. I've not really done much...
H: Efficient environment for machine or deep learning in Python I am getting very frustrated working with either Google Colab or Azure notebooks (they are very slow and glitchy). Usually, I work with Jupyter notebooks to perform Machine Learning or Deep Learning tasks in Python. Does anyone have any recommendations f...
H: Regression Trees - Splitting and decision rules I understand that a regression tree is built by splitting a node, such that the MSE for the label/output variable is minimized in each of the two resulting nodes. I have two questions about this: 1.) Is the search for the optimal split even dependent from the input va...
H: How to choose the model parameters (RandomizedSearchCV, .GridSearchCV) or manually Faced with the task of selecting parameters for the lightgbm model, the question accordingly arises, what is the best way to select them? I used the RandomizedSearchCV method, within 10 hours the parameters were selected, but there w...
H: What is the accuracy majority class classifier? I have an SFrame and a model: train_data,test_data = products.random_split(.8, seed=0) selected_words_model = graphlab.logistic_classifier.create(train_data, target='sentiment', ...
H: AWS : Workflow for deep learning I am using my company computer since I don't have another one or linux. Therefore, I am starting to use cloud resources to perform some tasks. I have a very simple question: Since most cloud resources don't have a GUI, how can I perform simple checks e.g. visualizing the bounding bo...
H: Do timesteps must have the same temporal distance in training a RNN? I have a recurrent neural network with LSTM units that I want to train with batches of 6 timesteps. Each timestep is a record of a dataset and represents the temporal aggregation over 5 minutes of data taken every 10 seconds. Unfortunately, the da...
H: What's the principal difference between ANN,RNN,DNN and CNN? I'm newer to deep learning domain. I would like to know what is the principal difference between RNN,ANN,DNN and CNN? How to implement those neural networks using the TensorFlow library? AI: Welcome to DS StackExchange. I'll go through your list: ANN (Ar...
H: Weighted Binary Cross Entropy Loss -- Keras Implementation I have a binary segmentation problem with highly imbalanced data such that there are almost 60 class zero samples for every class one sample. To address this issue, I coded a simple weighted binary cross entropy loss function in Keras with Tensorflow as the...
H: Evaluate imbalanced classification model on balanced testing sample Why it would be too optimistic to compute presicion, recall and f1-score to evaluate a model trained for imbalanced classification on a balanced testing sample ? AI: The test set should represent what your model will encounter in practice when you ...
H: Where to find height dataset, or datasets in General Hi there smart people, I am new to data Science and wanted to take my first few steps. Unfortunately I struggle to find datasets or any data at all regarding my topics of interest. For example, I wanted to build a simple program that takes a person's height and ...
H: How to use a a trained model I just trained my first model in Python 3.7/scikitlearn (Linear Regression) (well I copied most of the code but its something ^^). Now I want to actually Use the model. Specifically its about sons heights incorrelating to their fathers. So I now want to enter a new Father-height and get...
H: How to creat a plot for the accuracy of a model Iam pretty new to the whole topic so please dont be harsh. I know these may be simple questions but everybody has to start somewhere ^^ So I created (or more copied) my first little Model which predicts sons heights based on their fathers. #Father Data X=data['Father'...
H: Data Visualisation Techniques for Multi Labelled data I am new to data science and am trying to figure out how to visualize my multi labelled data using graphs. I am using a dataset to classify music by emotion based on their acoustic features (such as: pitch, amplitude etc.). So some have multi labelled emotion la...
H: Modelling of an environment that is stochastic in nature I have started learning reinforcement learning and have few doubts regarding model based and model free methods. Is it possible to model an environment that is stochastic in nature? Is it because its difficult to model such environment we use model free metho...
H: Simplest way to build a semantic analyzer I want to build a semantic analyzer i.e., to find how similar the meaning of two sentences are. For example- English: Birdie is washing itself in the water basin. English Paraphrase: The bird is bathing in the sink. Similarity Score: 5 ( The two sentences are completely eq...
H: Validity of cross-validation for model performance estimation When applying cross-validation for estimating the performance of a predictive model, the reported performance is usually the average performance over all the validation folds. As during this procedure, several models are created, one model has to be chos...