Support specifying missing value for tensor.tosparse()

[qinxuye]

Is your feature request related to a problem? Please describe.

For now, tensor.tosparse() will just treat 0 as missing value, we can allow specifying another missing value.

Describe the solution you'd like

e.g. support tensor.tosparse(missing=np.nan).

[smartguo]

can we set missing with multiple values? For example, tensor.tosparse(missing=[np.nan, -9999])

[qinxuye]

can we set missing with multiple values? For example, tensor.tosparse(missing=[np.nan, -9999])

Do you mean the value that is nan or -9999 will be treated as missing value?

[smartguo]

can we set missing with multiple values? For example, tensor.tosparse(missing=[np.nan, -9999])

Do you mean the value that is nan or -9999 will be treated as missing value?

Yes. But we can replace other value such as -9999 into np.nan in advance, I'm not sure which operation is better.

[qinxuye]

can we set missing with multiple values? For example, tensor.tosparse(missing=[np.nan, -9999])

Do you mean the value that is nan or -9999 will be treated as missing value?

Yes. But we can replace other value such as -9999 into np.nan in advance, I'm not sure which operation is better.

OK, I have already implemented it, missing can be multiple values, any of them will be treated as missing value.