How do i correctly predict the humidity values?
0
I have the following input:
startDate = "2013-01-01"
endDate = "2013-01-01"
knownTimestamps = ['2013-01-01 00:00','2013-01-01 01:00','2013-01-01 02:00','2013-01-01 03:00','2013-01-01 04:00',
'2013-01-01 05:00','2013-01-01 06:00','2013-01-01 08:00','2013-01-01 10:00','2013-01-01 11:00',
'2013-01-01 12:00','2013-01-01 13:00','2013-01-01 16:00','2013-01-01 17:00','2013-01-01 18:00',
'2013-01-01 19:00','2013-01-01 20:00','2013-01-01 21:00','2013-01-01 23:00']
humidity = ['0.62','0.64','0.62','0.63','0.63','0.64','0.63','0.64','0.48','0.46','0.45','0.44','0.46','0.47','0.48','0.49','0.51','0.52','0.52']
timestamps = ['2013-01-01 07:00','2013-01-01 09:00','2013-01-01 14:00','2013-01-01 15:00','2013-01-01 22:00']
And I am using following function to predict the humidity values using AR model in python.
from statsmodels.tsa.arima_model import ARIMA
def predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps):
data_prediction = pd.DataFrame({'knownTimestamps': knownTimestamps,'humidity': humidity})
print(data_prediction.head(10))
history = [float(x) for x in data_prediction.humidity]
predictions =
test = timestamps
for t in range(len(test)):
model = ARIMA(history, order=(2,2,0))
model_fit = model.fit(disp=0)
output = model_fit.forecast()
yhat = output[0]
predictions.append(float(yhat))
obs = test[t]
history.append(float(obs))
print(predictions)
return predictions
The model predict the same value of humidity for the values in time stamp list.
res = predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps)
print(res)
output = [0.5287247355700563, 0.5287247355700563, 0.5287247355700563,
0.5287247355700563, 0.5287247355700563]
Can someone tell me where I am wrong?
python time-series statsmodels arima
edited Nov 23 at 11:51
desertnaut
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
add a comment |
0
I have the following input:
startDate = "2013-01-01"
endDate = "2013-01-01"
knownTimestamps = ['2013-01-01 00:00','2013-01-01 01:00','2013-01-01 02:00','2013-01-01 03:00','2013-01-01 04:00',
'2013-01-01 05:00','2013-01-01 06:00','2013-01-01 08:00','2013-01-01 10:00','2013-01-01 11:00',
'2013-01-01 12:00','2013-01-01 13:00','2013-01-01 16:00','2013-01-01 17:00','2013-01-01 18:00',
'2013-01-01 19:00','2013-01-01 20:00','2013-01-01 21:00','2013-01-01 23:00']
humidity = ['0.62','0.64','0.62','0.63','0.63','0.64','0.63','0.64','0.48','0.46','0.45','0.44','0.46','0.47','0.48','0.49','0.51','0.52','0.52']
timestamps = ['2013-01-01 07:00','2013-01-01 09:00','2013-01-01 14:00','2013-01-01 15:00','2013-01-01 22:00']
And I am using following function to predict the humidity values using AR model in python.
from statsmodels.tsa.arima_model import ARIMA
def predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps):
data_prediction = pd.DataFrame({'knownTimestamps': knownTimestamps,'humidity': humidity})
print(data_prediction.head(10))
history = [float(x) for x in data_prediction.humidity]
predictions =
test = timestamps
for t in range(len(test)):
model = ARIMA(history, order=(2,2,0))
model_fit = model.fit(disp=0)
output = model_fit.forecast()
yhat = output[0]
predictions.append(float(yhat))
obs = test[t]
history.append(float(obs))
print(predictions)
return predictions
The model predict the same value of humidity for the values in time stamp list.
res = predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps)
print(res)
output = [0.5287247355700563, 0.5287247355700563, 0.5287247355700563,
0.5287247355700563, 0.5287247355700563]
Can someone tell me where I am wrong?
python time-series statsmodels arima
edited Nov 23 at 11:51
desertnaut
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
add a comment |
0
0
0
I have the following input:
startDate = "2013-01-01"
endDate = "2013-01-01"
knownTimestamps = ['2013-01-01 00:00','2013-01-01 01:00','2013-01-01 02:00','2013-01-01 03:00','2013-01-01 04:00',
'2013-01-01 05:00','2013-01-01 06:00','2013-01-01 08:00','2013-01-01 10:00','2013-01-01 11:00',
'2013-01-01 12:00','2013-01-01 13:00','2013-01-01 16:00','2013-01-01 17:00','2013-01-01 18:00',
'2013-01-01 19:00','2013-01-01 20:00','2013-01-01 21:00','2013-01-01 23:00']
humidity = ['0.62','0.64','0.62','0.63','0.63','0.64','0.63','0.64','0.48','0.46','0.45','0.44','0.46','0.47','0.48','0.49','0.51','0.52','0.52']
timestamps = ['2013-01-01 07:00','2013-01-01 09:00','2013-01-01 14:00','2013-01-01 15:00','2013-01-01 22:00']
And I am using following function to predict the humidity values using AR model in python.
from statsmodels.tsa.arima_model import ARIMA
def predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps):
data_prediction = pd.DataFrame({'knownTimestamps': knownTimestamps,'humidity': humidity})
print(data_prediction.head(10))
history = [float(x) for x in data_prediction.humidity]
predictions =
test = timestamps
for t in range(len(test)):
model = ARIMA(history, order=(2,2,0))
model_fit = model.fit(disp=0)
output = model_fit.forecast()
yhat = output[0]
predictions.append(float(yhat))
obs = test[t]
history.append(float(obs))
print(predictions)
return predictions
The model predict the same value of humidity for the values in time stamp list.
res = predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps)
print(res)
output = [0.5287247355700563, 0.5287247355700563, 0.5287247355700563,
0.5287247355700563, 0.5287247355700563]
Can someone tell me where I am wrong?
python time-series statsmodels arima
edited Nov 23 at 11:51
desertnaut
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
I have the following input:
startDate = "2013-01-01"
endDate = "2013-01-01"
knownTimestamps = ['2013-01-01 00:00','2013-01-01 01:00','2013-01-01 02:00','2013-01-01 03:00','2013-01-01 04:00',
'2013-01-01 05:00','2013-01-01 06:00','2013-01-01 08:00','2013-01-01 10:00','2013-01-01 11:00',
'2013-01-01 12:00','2013-01-01 13:00','2013-01-01 16:00','2013-01-01 17:00','2013-01-01 18:00',
'2013-01-01 19:00','2013-01-01 20:00','2013-01-01 21:00','2013-01-01 23:00']
humidity = ['0.62','0.64','0.62','0.63','0.63','0.64','0.63','0.64','0.48','0.46','0.45','0.44','0.46','0.47','0.48','0.49','0.51','0.52','0.52']
timestamps = ['2013-01-01 07:00','2013-01-01 09:00','2013-01-01 14:00','2013-01-01 15:00','2013-01-01 22:00']
And I am using following function to predict the humidity values using AR model in python.
from statsmodels.tsa.arima_model import ARIMA
def predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps):
data_prediction = pd.DataFrame({'knownTimestamps': knownTimestamps,'humidity': humidity})
print(data_prediction.head(10))
history = [float(x) for x in data_prediction.humidity]
predictions =
test = timestamps
for t in range(len(test)):
model = ARIMA(history, order=(2,2,0))
model_fit = model.fit(disp=0)
output = model_fit.forecast()
yhat = output[0]
predictions.append(float(yhat))
obs = test[t]
history.append(float(obs))
print(predictions)
return predictions
The model predict the same value of humidity for the values in time stamp list.
res = predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps)
print(res)
output = [0.5287247355700563, 0.5287247355700563, 0.5287247355700563,
0.5287247355700563, 0.5287247355700563]
Can someone tell me where I am wrong?
python time-series statsmodels arima
python time-series statsmodels arima
edited Nov 23 at 11:51
desertnaut
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
edited Nov 23 at 11:51
desertnaut
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
edited Nov 23 at 11:51
desertnaut
16.2k63566
edited Nov 23 at 11:51
desertnaut
16.2k63566
edited Nov 23 at 11:51
desertnaut
16.2k63566
16.2k63566
asked Nov 23 at 0:02
CEXDSINGH
133
asked Nov 23 at 0:02
CEXDSINGH
133
asked Nov 23 at 0:02
CEXDSINGH
133
133
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
0
You are not updating your history. Presumably, this is the site where most of your code comes from
https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/
There you can see how, on line 23, the history is updated and used for the forecast at the next step on the test set:
history.append(obs)
answered Nov 23 at 0:13
Phoenix87
242312
It didnt worked. I added these two lines.obs = test[t]; history.append(obs)
– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.history.append(float(obs))Still doesn't work
– CEXDSINGH
Nov 23 at 0:37
add a comment |
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1 Answer
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1 Answer
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active
oldest
votes
active
oldest
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active
oldest
votes
0
You are not updating your history. Presumably, this is the site where most of your code comes from
https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/
There you can see how, on line 23, the history is updated and used for the forecast at the next step on the test set:
history.append(obs)
answered Nov 23 at 0:13
Phoenix87
242312
It didnt worked. I added these two lines.obs = test[t]; history.append(obs)
– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.history.append(float(obs))Still doesn't work
– CEXDSINGH
Nov 23 at 0:37
add a comment |
0
You are not updating your history. Presumably, this is the site where most of your code comes from
https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/
There you can see how, on line 23, the history is updated and used for the forecast at the next step on the test set:
history.append(obs)
answered Nov 23 at 0:13
Phoenix87
242312
It didnt worked. I added these two lines.obs = test[t]; history.append(obs)
– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.history.append(float(obs))Still doesn't work
– CEXDSINGH
Nov 23 at 0:37
add a comment |
0
0
0
You are not updating your history. Presumably, this is the site where most of your code comes from
https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/
There you can see how, on line 23, the history is updated and used for the forecast at the next step on the test set:
history.append(obs)
answered Nov 23 at 0:13
Phoenix87
242312
You are not updating your history. Presumably, this is the site where most of your code comes from
https://machinelearningmastery.com/arima-for-time-series-forecasting-with-python/
There you can see how, on line 23, the history is updated and used for the forecast at the next step on the test set:
history.append(obs)
answered Nov 23 at 0:13
Phoenix87
242312
answered Nov 23 at 0:13
Phoenix87
242312
answered Nov 23 at 0:13
Phoenix87
242312
answered Nov 23 at 0:13
Phoenix87
242312
242312
It didnt worked. I added these two lines.obs = test[t]; history.append(obs)
– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.history.append(float(obs))Still doesn't work
– CEXDSINGH
Nov 23 at 0:37
add a comment |
It didnt worked. I added these two lines.obs = test[t]; history.append(obs)
– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.history.append(float(obs))Still doesn't work
– CEXDSINGH
Nov 23 at 0:37
It didnt worked. I added these two lines.
obs = test[t]; history.append(obs)– CEXDSINGH
Nov 23 at 0:17
It didnt worked. I added these two lines.
obs = test[t]; history.append(obs)– CEXDSINGH
Nov 23 at 0:17
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
your test variable contains timestamps while your history contains floats. You should fix that too.
– Phoenix87
Nov 23 at 0:22
casted it to float.
history.append(float(obs)) Still doesn't work– CEXDSINGH
Nov 23 at 0:37
casted it to float.
history.append(float(obs)) Still doesn't work– CEXDSINGH
Nov 23 at 0:37
add a comment |
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