From 95132f18ef5c909f077153bc863d03cc5bacbffd Mon Sep 17 00:00:00 2001
From: amilabluetelecoms <amila@bluetelecoms.com>
Date: Tue, 15 Nov 2022 02:58:56 +0000
Subject: [PATCH] lstm
---
lstm_model.py | 29 +++++++++++++++++++++++++++++
1 file changed, 29 insertions(+)
diff --git a/lstm_model.py b/lstm_model.py
index e69de29..3037d0f 100644
--- a/lstm_model.py
+++ b/lstm_model.py
@@ -0,0 +1,29 @@
+from pandas import DataFrame
+from pandas import concat
+
+def series_to_supervised(data, n_in=1, n_out=1, dropnan=True):
+ n_vars = 1 if type(data) is list else data.shape[1]
+ df = DataFrame(data)
+ cols, names = list(), list()
+ # input sequence (t-n, ... t-1)
+ for i in range(n_in, 0, -1):
+ cols.append(df.shift(i))
+ names += [('var%d(t-%d)' % (j+1, i)) for j in range(n_vars)]
+ # forecast sequence (t, t+1, ... t+n)
+ for i in range(0, n_out):
+ cols.append(df.shift(-i))
+ if i == 0:
+ names += [('var%d(t)' % (j+1)) for j in range(n_vars)]
+ else:
+ names += [('var%d(t+%d)' % (j+1, i)) for j in range(n_vars)]
+ # put it all together
+ agg = concat(cols, axis=1)
+ agg.columns = names
+ # drop rows with NaN values
+ if dropnan:
+ agg.dropna(inplace=True)
+ return agg
+
+
+
+
--
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