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authorbloodstalker <thabogre@gmail.com>2018-09-29 12:30:44 +0000
committerbloodstalker <thabogre@gmail.com>2018-09-29 12:30:44 +0000
commit3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8 (patch)
tree6feaa17b0feaf4f941720d85507d77add869288f /lstm.py
parentupdate (diff)
downloadseer-3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8.tar.gz
seer-3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8.zip
update
Diffstat (limited to 'lstm.py')
-rwxr-xr-xlstm.py6
1 files changed, 4 insertions, 2 deletions
diff --git a/lstm.py b/lstm.py
index f27b892..765b0e1 100755
--- a/lstm.py
+++ b/lstm.py
@@ -2,6 +2,8 @@
# _*_ coding=utf-8 _*_
#original source:https://github.com/dashee87/blogScripts/blob/master/Jupyter/2017-11-20-predicting-cryptocurrency-prices-with-deep-learning.ipynb
+#@#!pip install lxml
+#@#!mkdir lstm-models
import argparse
import code
import readline
@@ -134,10 +136,10 @@ def load_models(crypto, crypto_short):
def premain(argparser):
signal.signal(signal.SIGINT, SigHandler_SIGINT)
#here
- #lstm_type_1("ethereum", "ether")
+ lstm_type_1("ethereum", "ether")
#lstm_type_2("ethereum", "ether", 5, 20)
#lstm_type_3("ethereum", "ether", 5, 20)
- load_models("ethereum", "eth")
+ #load_models("ethereum", "eth")
def main():
argparser = Argparser()