Tag Archives: Data Science

I need to build up a predictive modelling to get prediction of the month to month sales for given geological district

In this predictive modelling, only three techniques are allowed i.e. Linear regression , Decision Tree , Naive Bayes. Here is the some code on behalf of my practice because I’m totally new to machine learning… import pandas as pd import matplotlib.pyplot as plt import numpy as np import seaborn as sb from sklearn.linear_model import LinearRegression… Read More »

How to give weight to features manually

I have a dataset with continuous label ranges from one to five with nine different features.So I wanted to give weight to each feature manually because some of the features have very less dependency in the label so I wanted to give more weight to those features which have more dependency in the label.so how… Read More »

Calculating correlation of slightly out of sync data

I am trying to do some analysis on some data that comes from special glasses that track a few things including pupil size and gaze velocity. I would like to calculate the correlation between two glasses on two different people. At the moment I cannot use df.correlate() because the timestamps are not identical and therefore… Read More »

data preprosesing for recovery symbols

I am going to use RNN encoder/decoder to recovery space-characters(‘ ‘) in text. Input vector is sequence of characters encoded as bag of characters. [162,85,45] Output vector is mask which show places for space-characters. [0,0,1,0] It means that in final sequence should be space between character(code 85) and character(code 45). Will it work? if yes… Read More »

Pre-train using sigmoid and train using ReLU?

Using RBMs to pre-train a deep net as in this example RBM, the activation function is sigmoid and makes the math much easier. What are the implications after the initial weights are learned using sigmoid activation functions to switch to ReLU for the train phase? I suppose that using tanh in either phase (pre-train or… Read More »

generating training samples for an RNN

I am trying to learn how an recurrent neural network (RNN) is trained. I have read chapter 10 of the book by Goodfellow, Bengio and Courville and various tutorials on the internet. If I understand right, RNNs are usually trained by unrolling a fixed-length stretch of the recursion, say of length $n$, and then training… Read More »