All Questions
74 questions
0
votes
2
answers
78
views
why the output of filtering pandas file becomes NaN?
I want the output becomes non NaN value.
the problem in this line
f_bp_max.loc[l, 'max'] = df_frcst[df_frcst['Datetime'].dt.year == k]['Forecast'].max()
When I print this:
df_frcst[df_frcst['Datetime'...
- 11
0
votes
1
answer
100
views
Tensorflow Keras ValueError: Unexpected result of `predict_function` (Empty batch_outputs)
I am trying to train some machine learning models to predict the price action for 4 chosen stocks from a list of NASDAQ-100 stocks.
I am very new to Python, so I've run into a few issues I have not ...
- 19
0
votes
0
answers
43
views
What is the difference between Sequential and Concatenate of keras while creating input for model?
What is the difference between Sequential and Concatenate of keras while creating input for model?
I have seen two way of creating layers with Sequential where we just define the shape of the input, ...
- 1,035
-1
votes
1
answer
23
views
What happens while predicting using a model when preprocessing layer is inside the model itself?
While training if we apply preprocessing like horizontal flip inside the model itself won't it affect the data while its predicting?
so whats a work around to this or will it not matter if the ...
- 1
0
votes
1
answer
191
views
Inverse Standardization of predicted values
I've dataset with two columns. At first I've split the data into train, val and test and after that I've standardized all the data (train, val and test).
train_mean = train_data.mean()
train_std = ...
- 303
0
votes
1
answer
53
views
is there a way to make this more efficient, iterating through rows in a data frame
I want to iterate through the rows of my data frame and extract the values from the rows into variables and then append that into arrays. the df is very long, about 30,000.
I read online that you can ...
-1
votes
1
answer
58
views
How to Convert Data Where Inputs/Features Have Different Shapes to a Dataset?
Example raw data where it's a List of Dict:
data = [
{
input1: 'Hello',
input2: -100,
input3: [1, 2, 3],
target: 1
},
...
]
How do I convert this to a TensorFlow dataset using ...
- 145
0
votes
1
answer
126
views
How remove the label data from feature data from window time series (tensorflow)
I train a models of time series forecasting use tensorflow. The models in this tutorial will make a set of predictions based on a window of consecutive samples from the data.
*I want to remove the ...
0
votes
1
answer
140
views
LSTM train data resample
I try train LSTM model with time series data.
If I load it as they are everything is ok. Model work with good accuracy and loss function.
But if I resample it for example 1H or 24H it stop work. ...
- 651
1
vote
1
answer
129
views
Assertion failed error in Tensorflow linear regression model
# IMPORTS
import os
import numpy as np
import tensorflow as tf
import pandas as pd
# IMPORT CSV FILES AS PANDASDB
dfTrain = pd.read_csv('carPriceTrain.csv')
dfEval = pd.read_csv('carPriceEval.csv')
#...
- 23
2
votes
0
answers
71
views
Tf.data.Dataset store a array column Error
Is there any way to store inside a tf.data.Dataset formed from a pandas dataframe, a column where each cell corresponds to an array of floats?
I have a pandas dataframe where a column has a list of ...
- 41
0
votes
1
answer
621
views
ValueError when fitting my model. (ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224,3,3))
I am new to machine learning and I am using kaggle's notebook to code. I am making a classification model with multiple categories. I used efficientnet to make my model's architecture but the issue ...
- 21
2
votes
1
answer
363
views
How to process .csv for time series classification
I was wondering how to handle the recorded time series data to feed it into a RNN.
I want to take the data of 16 time steps and the labels of 15 to make the RNN classify the 16th time step(if that ...
1
vote
1
answer
1k
views
How to predict future days with fbprophet for multivariate data?
I have trained the fbprophet model using multivariate data for 80% of train data and 20% test. I would like to train and predict data for 5 days into the future, using the same multivariate approach. ...
- 47
-1
votes
1
answer
76
views
Dataframe users who did not purchase item for user-item collaborative filtering [closed]
I intend to use a hybrid user-item collaborative filtering to build a Top-N recommender system with TensorFlow Keras
currently my dataframe consist of |user_id|article_id|purchase
purchase is always ...
- 593