[Help] recommend top 10 items for a particular item?

[karthikraja95]

Hi all,

@amoussawi

I am following the tutorial, but I am using my own data set, the format is the same as the movie lens dataset except I don't have a timestamp. I have userId, itemid, ratings (purchase count as a rating).

I used the following the code

from recoder.model import Recoder from recoder.data import RecommendationDataset from recoder.nn import DynamicAutoencoder from recoder.metrics import AveragePrecision, Recall, NDCG

import scipy.sparse as sparse

train_matrix = sparse.load_npz('train.npz')

val_input_matrix = sparse.load_npz('test_input.npz') val_target_matrix = sparse.load_npz('test_target.npz')

train_dataset = RecommendationDataset(train_matrix)

val_dataset = RecommendationDataset(val_input_matrix, val_target_matrix)

model = DynamicAutoencoder(hidden_layers=[200], activation_type='tanh', noise_prob=0.5, sparse=True)

metrics = [Recall(k=20, normalize=True), Recall(k=50, normalize=True), NDCG(k=100)]

recoder = Recoder(model=model, use_cuda=False, optimizer_type='adam', loss='logistic')

recoder.train(train_dataset=train_dataset, val_dataset=val_dataset, batch_size=500, lr=1e-3, weight_decay=2e-5, num_epochs=100, num_data_workers=4, negative_sampling=True, metrics=metrics, eval_num_recommendations=100)

It ran. Now I want to recommend the top 10 items for a particular userid or for all userid? How do I do that?

I tried the below code:

from recoder.recommender import InferenceRecommender recommendation = InferenceRecommender(recoder,100)

what do I pass inside recommendation.recommend(------)?

or is there any other way to recommend top 10 items for a particular userid or for all userid?

Any help would be appreciated

Thanks

[karthikraja95]

Solved it.