Accurately choosing a model with sequential data Unicorn Meta Zoo #1: Why another podcast? Announcing the arrival of Valued Associate #679: Cesar Manara 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsMulticlass classification with large number of classes but for each user the set of target classes is knownChoosing an algorithm with normalized data(Classification)Choosing data clustering method to visualize dataLearning with groups of sequential dataPreparing data, choosing algorithmloss = function(iteration) gets super wobbly once it gets near the bottomWhich tool should I use for combining this large dataset?Model Joint Probability of N Words Appearing Together in a Sentencehelp with Keras sequential model outputMerging dataframes in Pandas is taking a surprisingly long time
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Accurately choosing a model with sequential data
Unicorn Meta Zoo #1: Why another podcast?
Announcing the arrival of Valued Associate #679: Cesar Manara
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsMulticlass classification with large number of classes but for each user the set of target classes is knownChoosing an algorithm with normalized data(Classification)Choosing data clustering method to visualize dataLearning with groups of sequential dataPreparing data, choosing algorithmloss = function(iteration) gets super wobbly once it gets near the bottomWhich tool should I use for combining this large dataset?Model Joint Probability of N Words Appearing Together in a Sentencehelp with Keras sequential model outputMerging dataframes in Pandas is taking a surprisingly long time
$begingroup$
The dataset I'm working on is mapping journeys - breaking them down into entry & exit coordinates, and entry & exit times, for each part of the journey. My goal is to predict the final exit coordinates, given the final time (though I'm not 100% sure time matters).
I'm having an issue finding an appropriate model that takes the time features into account. At the moment, rather than predicting this final location (x,y coordinate), I'm using a catboost classifier to tell me whether the final location of each user will be in a given area or not, but I'm not sure if I'm barking up the wrong tree. A problem I have is when I flatten the data (which I feel I need to?), I have a lot of NaN values, because each journey is a different number of trajectories added together (up to 20).
I was doing a little research and found some papers on applying neural nets (specifically RNNs) to this kind of data, but my knowledge of NNs is rather incomplete.
What sort of model might I try to better fit my data? Would I be best off getting to grips with RNNs?
machine-learning dataset data-cleaning
asked Apr 5 at 10:57
A BerryA Berry
12
$endgroup$
add a comment |
$begingroup$
The dataset I'm working on is mapping journeys - breaking them down into entry & exit coordinates, and entry & exit times, for each part of the journey. My goal is to predict the final exit coordinates, given the final time (though I'm not 100% sure time matters).
I'm having an issue finding an appropriate model that takes the time features into account. At the moment, rather than predicting this final location (x,y coordinate), I'm using a catboost classifier to tell me whether the final location of each user will be in a given area or not, but I'm not sure if I'm barking up the wrong tree. A problem I have is when I flatten the data (which I feel I need to?), I have a lot of NaN values, because each journey is a different number of trajectories added together (up to 20).
I was doing a little research and found some papers on applying neural nets (specifically RNNs) to this kind of data, but my knowledge of NNs is rather incomplete.
What sort of model might I try to better fit my data? Would I be best off getting to grips with RNNs?
machine-learning dataset data-cleaning
asked Apr 5 at 10:57
A BerryA Berry
12
$endgroup$
add a comment |
$begingroup$
The dataset I'm working on is mapping journeys - breaking them down into entry & exit coordinates, and entry & exit times, for each part of the journey. My goal is to predict the final exit coordinates, given the final time (though I'm not 100% sure time matters).
I'm having an issue finding an appropriate model that takes the time features into account. At the moment, rather than predicting this final location (x,y coordinate), I'm using a catboost classifier to tell me whether the final location of each user will be in a given area or not, but I'm not sure if I'm barking up the wrong tree. A problem I have is when I flatten the data (which I feel I need to?), I have a lot of NaN values, because each journey is a different number of trajectories added together (up to 20).
I was doing a little research and found some papers on applying neural nets (specifically RNNs) to this kind of data, but my knowledge of NNs is rather incomplete.
What sort of model might I try to better fit my data? Would I be best off getting to grips with RNNs?
machine-learning dataset data-cleaning
asked Apr 5 at 10:57
A BerryA Berry
12
$endgroup$
The dataset I'm working on is mapping journeys - breaking them down into entry & exit coordinates, and entry & exit times, for each part of the journey. My goal is to predict the final exit coordinates, given the final time (though I'm not 100% sure time matters).
I'm having an issue finding an appropriate model that takes the time features into account. At the moment, rather than predicting this final location (x,y coordinate), I'm using a catboost classifier to tell me whether the final location of each user will be in a given area or not, but I'm not sure if I'm barking up the wrong tree. A problem I have is when I flatten the data (which I feel I need to?), I have a lot of NaN values, because each journey is a different number of trajectories added together (up to 20).
I was doing a little research and found some papers on applying neural nets (specifically RNNs) to this kind of data, but my knowledge of NNs is rather incomplete.
What sort of model might I try to better fit my data? Would I be best off getting to grips with RNNs?
machine-learning dataset data-cleaning
machine-learning dataset data-cleaning
asked Apr 5 at 10:57
A BerryA Berry
12
asked Apr 5 at 10:57
A BerryA Berry
12
edited Apr 5 at 11:13
A Berry
asked Apr 5 at 10:57
A BerryA Berry
12
asked Apr 5 at 10:57
A BerryA Berry
12
asked Apr 5 at 10:57
A BerryA Berry
12
12
add a comment |
add a comment |
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