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Merge branch 'master' of https://github.com/titanscout2022/tr2022-strategy

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This commit is contained in:
Jacob Levine 2019-03-16 15:49:49 -05:00
commit f483cbbcfb
5 changed files with 9 additions and 19 deletions
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5
data analysis/data/aSetOfData.csv
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data analysis/data/bdata.csv
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5
data analysis/data/data.csv
View File

@ -1,5 +0,0 @@
1,2,3,4,5,6,7,8
5,6,7,8,9,10,11,12
1000,2000,3000,4000,5000,6000,7000,8000
0,0,0,0,0,0,0,1
3,5,6,7,8.5,9.8,11.1,12.4
1 1 2 3 4 5 6 7 8
2 5 6 7 8 9 10 11 12
3 1000 2000 3000 4000 5000 6000 7000 8000
4 0 0 0 0 0 0 0 1
5 3 5 6 7 8.5 9.8 11.1 12.4

2
data analysis/superscript.py
View File

@ -38,7 +38,7 @@ __author__ = (
"Arthur Lu <arthurlu@ttic.edu>, "
"Jacob Levine <jlevine@ttic.edu>,"
)
s
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore

11
data analysis/titanlearn.py
View File

@ -30,9 +30,10 @@ from sklearn import metrics, datasets
import numpy as np
import matplotlib.pyplot as plt
import math
import time
#enable CUDA if possible
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
device = torch.device("cpu")
#linear_nn: creates a fully connected network given params
def linear_nn(in_dim, hidden_dim, out_dim, num_hidden, act_fn="tanh", end="none"):
@ -194,8 +195,12 @@ def retyuoipufdyu():
data = torch.tensor(datasets.fetch_california_housing()['data']).to(torch.float)
ground = datasets.fetch_california_housing()['target']
ground=torch.tensor(ground).to(torch.float)
ground = torch.tensor(ground).to(torch.float)
model = linear_nn(8, 100, 1, 20, act_fn = "relu")
print(model)
return train_sgd_simple(model,"regression", data, ground, learnrate=1e-4, iters=1000)
#retyuoipufdyu()
start = time.time()
retyuoipufdyu()
end = time.time()
print(end-start)